WO2021114779A1 - 基于双端发声检测的回声消除方法、装置及系统 - Google Patents

基于双端发声检测的回声消除方法、装置及系统 Download PDF

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WO2021114779A1
WO2021114779A1 PCT/CN2020/114168 CN2020114168W WO2021114779A1 WO 2021114779 A1 WO2021114779 A1 WO 2021114779A1 CN 2020114168 W CN2020114168 W CN 2020114168W WO 2021114779 A1 WO2021114779 A1 WO 2021114779A1
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signal
input sound
utterance
sound signal
double
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French (fr)
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潘思伟
罗本彪
雍雅琴
董斐
林福辉
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Spreadtrum Communications Shanghai Co Ltd
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Spreadtrum Communications Shanghai Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04M—TELEPHONIC COMMUNICATION
    • H04M9/00—Arrangements for interconnection not involving centralised switching
    • H04M9/08—Two-way loud-speaking telephone systems with means for conditioning the signal, e.g. for suppressing echoes for one or both directions of traffic
    • H04M9/082—Two-way loud-speaking telephone systems with means for conditioning the signal, e.g. for suppressing echoes for one or both directions of traffic using echo cancellers
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04M—TELEPHONIC COMMUNICATION
    • H04M9/00—Arrangements for interconnection not involving centralised switching
    • H04M9/08—Two-way loud-speaking telephone systems with means for conditioning the signal, e.g. for suppressing echoes for one or both directions of traffic
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/0208—Noise filtering
    • G10L21/0216—Noise filtering characterised by the method used for estimating noise
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/0208—Noise filtering
    • G10L2021/02082—Noise filtering the noise being echo, reverberation of the speech

Definitions

  • This application relates to the field of voice communication, and in particular to an echo cancellation method, device and system based on double-ended voice detection.
  • the acoustic echo is due to the coupling between the speaker and the terminal microphone, resulting in the telephone microphone not only containing useful voice signals, but also echo. If the microphone signal is not processed, the echo signal and the near-end voice signal will be transmitted to the far-end speaker for playback, and the far-end caller will hear his delayed voice, which will make people feel uncomfortable and affect the call Effect. When the echo is loud, the call cannot even be carried out normally. Therefore, effective measures must be taken to suppress the echo and eliminate its impact in order to improve the quality of voice communication.
  • Echo cancellation has become an engineering problem that needs to be solved since Bell invented the telephone.
  • communication methods and application scenarios have become increasingly diversified, and communication terminals have become more and more compact, making the coupling between speakers and microphones stronger and stronger, and the echo channel has become more and more complex and changeable. This is voice communication.
  • Acoustic echo cancellation in the system poses a great challenge.
  • Acoustic echo is generally produced in hands-free communication systems. It is an echo generation method affected by sound wave propagation. Generally, it can be divided into two situations: direct echo and indirect echo.
  • Direct echo means that the sound played by the speaker directly enters the microphone along the path without any reflection and is picked up. This echo has the shortest delay time, and the voice energy of the far-end speaker, the distance and angle between the speaker and the microphone, and the speaker The playback volume and the pickup sensitivity of the microphone are related to other factors.
  • Indirect echo refers to the collection of echoes generated by the sound played by the speaker entering the microphone after being reflected one or more times through different paths. The characteristics of this echo are long delay time, large delay jitter, and the amount of echo that is greatly affected by the environment.
  • an adaptive echo canceller (Acoustic Echo Canceller, AEC for short) is usually used to cancel the echo.
  • AEC Acoustic Echo Canceller
  • the basic principle of AEC can be summarized as adaptively estimating the echo and subtracting the estimated echo from the signal picked up by the microphone.
  • AEC can avoid the influence of echo between the callers; in the hands-free phone, AEC can minimize the echo.
  • the echo cancellation effect of AEC can meet the current needs; however, when there is obvious near-end sound, the performance of AEC based on various existing adaptive filtering algorithms will deteriorate, and it cannot even guarantee self-control. Adapt to the convergence of the filtering algorithm.
  • double-talk detector DTD
  • a typical application of DTD is to freeze AEC updates during double-talk periods to prevent adaptive filtering algorithms. Divergence.
  • the double-ended utterance detection algorithm may specifically include an energy-based double-ended utterance detection algorithm, a double-ended utterance detection algorithm based on signal correlation characteristics, and a double-ended utterance detection algorithm based on spectral characteristics.
  • These double-ended vocalization detection algorithms all rely on the selection of a fixed threshold, and the vocalization state is judged by comparing the calculated statistics with the threshold.
  • the fixed threshold method cannot accurately detect the double-ended voice state. This not only affects the robustness of echo cancellation, but also produces severe sound cuts during subsequent processing, that is, the sound transmitted to the remote user will be intermittent.
  • the main influencing factor in hands-free communication equipment is the signal-to-return ratio of the signal received by the microphone, that is, the amplitude (power) ratio of the near-end voice received by the microphone to the echo signal received from the speaker.
  • the microphone's response ratio is usually lower during hands-free calls, and the distance between the microphone and the near-end talker, the volume of the near-end talker, and the size of the echo will change the return ratio. This makes the traditional The double-ended voice detection algorithm based on a fixed threshold often fails, and it is difficult to balance the duplex and de-echo performance in hands-free calling.
  • the echo cancellation technology in the prior art cannot accurately filter out the echo interference in double-ended voice problems, especially in hands-free calls and conference calls, and the call quality is easily affected.
  • the technical problem solved by this application is how to better eliminate echo and improve the duplex call experience of the hands-free voice communication terminal.
  • embodiments of the present application provide an echo cancellation method, device, and system based on double-ended vocalization detection, where the echo cancellation method based on double-ended vocalization detection may include: acquiring an input sound signal from a sound collection device; Perform adaptive filtering on the input sound signal to obtain a near-end speech estimation signal; determine the current utterance state according to the near-end speech estimation signal; obtain a preset mapping relationship between the utterance state and the processing mode, according to the The mapping relationship obtains the processing mode corresponding to the current utterance state; processes the near-end speech estimation signal according to the processing mode; and outputs the processed near-end speech estimation signal to obtain an output signal.
  • the determining the current utterance state according to the near-end speech estimation signal includes: calculating the double-ended utterance state of the current frame in the input sound signal according to the input sound signal and the near-end speech estimation signal The average value of the statistics; obtain the dual-speaker judgment threshold corresponding to the current frame, the dual-speaker judgment threshold is obtained according to the signal-to-return ratio of the input sound signal and the near-end interference signal; according to the double-end utterance of the current frame The relationship between the average value of the state statistics and the dual-talk judgment threshold is used to determine the current utterance state.
  • the calculating the average value of the double-ended utterance state statistics of the current frame in the input sound signal according to the input sound signal and the near-end speech estimation signal includes: calculating the current state according to the following formula The average value of the double-ended utterance state statistics of the frame: where, is the average value of the double-ended utterance state statistics of the current frame, represents the power of the near-end speech estimation signal at the kth frame and the nth sample point, and represents the total The power of the input sound signal in the k-th frame and the n-th sample point represents the average value of the values in the brackets.
  • the obtaining the dual-talk judgment threshold corresponding to the current frame includes: real-time estimation of the input sound signal To obtain the average response ratio of the current frame in the input sound signal; obtain multiple preset thresholds for the response ratio, and construct multiple response ratio intervals according to the multiple thresholds; Determine the interval of the average response ratio of the current frame to which the average response ratio belongs, and obtain the dual-speaking judgment threshold corresponding to the interval of the said current frame as the dual-speaking judgment threshold of the current frame.
  • the real-time estimation of the signal return ratio of the input sound signal to obtain the average signal return ratio of the current frame in the input sound signal includes: acquiring a near-end interference signal, where the near-end interference signal is and The sound signal generated by the sound generating device at the same end of the sound collection device; calculate the average response ratio of the current frame in the input sound signal according to the following formula; wherein, represents the estimated average response ratio of the k-th frame, Its unit is dB, which represents the power of the input sound signal at the k-th frame and the n-th sample point, represents the power of the near-end interference signal at the k-th frame and the n-th sample point, and represents the value in brackets average value.
  • the acquiring multiple preset thresholds of the return ratio, and constructing multiple intervals of the return ratio according to the multiple thresholds includes: comparing the acquired multiple thresholds with the return ratio. The two adjacent ones are used as the boundary value of the RR interval to obtain multiple RL interval.
  • the utterance state includes two states: only the far-end utterance and not only the far-end utterance, and the preset mapping relationship between the utterance state and the processing mode includes: when the utterance state is only the far-end utterance, Performing zeroing processing on the near-end speech estimation signal or suppressing it to be inaudible; when the utterance state is judged to be not only the far-end utterance, the near-end speech estimation signal is retained.
  • the not only far-end utterance includes two states: near-end utterance only and double-ended utterance.
  • the performing adaptive filtering on the input sound signal to obtain the near-end speech estimation signal includes: performing linear filtering and non-linear filtering on the input sound signal, respectively, to obtain the near-end speech estimation signal.
  • An embodiment of the present application also provides an echo cancellation device based on double-ended vocalization detection.
  • the device includes: an input sound signal acquisition module for acquiring an input sound signal from a sound collection device; a filtering module for evaluating the input sound The signal is adaptively filtered to obtain the near-end speech estimation signal; the current utterance state determination module is used to determine the current utterance state according to the near-end speech estimation signal; the processing method acquisition module is used to obtain the preset utterance state and The mapping relationship between the processing modes, the processing mode corresponding to the current utterance state is obtained according to the mapping relationship; a near-end processing module, configured to process the near-end speech estimation signal according to the processing mode; an output module , Used to output the processed near-end speech estimation signal to obtain an output signal.
  • the embodiment of the present application also provides an echo cancellation system based on double-ended voice detection, including a sound collection device, a same-end voice device, and an echo cancellation device, and the echo cancellation device executes the steps of any one of the above-mentioned methods.
  • An embodiment of the present application provides an echo cancellation method based on double-ended utterance detection.
  • the method includes: acquiring an input sound signal from a sound collection device; adaptively filtering the input sound signal to obtain a near-end speech estimation signal; Determine the current utterance state according to the near-end speech estimation signal; obtain the mapping relationship between the preset utterance state and the processing mode, and obtain the processing mode corresponding to the current utterance state according to the mapping relationship;
  • the near-end speech estimation signal is processed in a manner; the processed near-end speech estimation signal is output to obtain an output signal.
  • the input sound signal in a voice call such as a telephone is different from the direct transmission to the peer device in the existing communication scheme or only the adaptive echo cancellation is transmitted to the peer device.
  • the technical scheme in this method Customize different processing methods according to different sounding states corresponding to the input sound signal, and accurately filter out the echo in the input sound signal by combining the characteristics of double-ended sounding. Especially in the call system that is greatly affected by the interference of double-end vocalization, such as hands-free call and voice conference, the call quality can be significantly improved.
  • the real-time sounding state judgment is performed on each frame of the input sound signal to realize the real-time update of the processing method of the near-end voice estimation signal, so that the input sound signal can be accurately and completely echo canceled, and the call can be guaranteed. Stability of the process.
  • the signal-to-return ratio of the input sound signal with the near-end interference signal as the echo source is calculated in real time by sampling, and different dual-talk judgment thresholds are set when the influence of the near-end interference signal on the input sound signal is different. It can more accurately determine the current sounding state and improve the accuracy of echo cancellation for the input sound signal.
  • two utterance states are defined, and processing methods corresponding to the two utterance states are specified, which can basically meet the requirements of real-time echo cancellation in common voice calls.
  • the adaptive filtering of the input sound signal includes two operations of linear filtering and non-linear filtering, which can further suppress the echo of the input sound signal.
  • the echo cancellation system based on double-ended vocalization detection provided by the embodiments of the present application can perform real-time detection based on the acoustic echo generated in the communication process, and eliminate it based on the detection result, so that the echo cancellation system can be improved when the voice communication terminal is in the hands-free mode. Eliminate the effect to improve the quality of the call.
  • the echo cancellation method, device and system based on double-ended utterance detection provided in the embodiments of the present application can distinguish between only far-end utterance and only near-end utterance or double-ended utterance in real time.
  • the time-domain output result is zeroed or suppressed to inaudible, so that the echo can be eliminated to the greatest extent while ensuring the duplex call performance, so as to improve the echo cancellation and duplex performance at the same time.
  • the purpose is to improve the duplex call experience of the hands-free voice communication terminal.
  • FIG. 1 is a schematic flowchart of an echo cancellation method based on double-ended vocalization detection according to an embodiment of the present application
  • FIG. 2 is a schematic diagram of the application of an echo cancellation method based on double-ended vocalization detection according to an embodiment of the present application
  • FIG. 3 is a schematic flowchart of step S103 in FIG. 1 in an embodiment of the present application.
  • FIG. 4 is a schematic flowchart of step S302 in FIG. 3 in an embodiment of the present application.
  • FIG. 5 is a schematic diagram of a response ratio interval according to an embodiment of the present application.
  • FIG. 6 is a schematic structural diagram of an echo cancellation device based on double-ended vocalization detection according to an embodiment of the present application
  • FIG. 7 is a schematic structural diagram of an echo cancellation system based on double-ended vocalization detection according to an embodiment of the present application.
  • the echo cancellation technology in the prior art cannot accurately filter out the echo interference in double-ended voice problems, especially in hands-free calls and conference calls, and the call quality is easily affected.
  • an embodiment of the present application provides an echo cancellation method based on double-ended vocalization detection.
  • the method includes: acquiring an input sound signal from a sound collection device; performing adaptive filtering on the input sound signal to obtain a close End speech estimation signal; determine the current utterance state according to the near-end speech estimation signal; obtain the mapping relationship between the preset utterance state and processing mode, and obtain the processing mode corresponding to the current utterance state according to the mapping relationship ; Process the near-end speech estimation signal according to the processing mode; output the processed near-end speech estimation signal to obtain an output signal.
  • Adopting the solution described in this embodiment can filter out the interference signal in the double-ended voice, and significantly improve the quality of the call.
  • Figure 1 provides a schematic flow chart of an echo cancellation method based on double-ended vocalization detection; the method may specifically include the following steps:
  • S101 Obtain an input sound signal from a sound collection device.
  • the input sound signal is the sound signal collected by the sound collection device.
  • the sound collection device may be a microphone or other device, and for a telephone or phone-like call, it is a sound collection device that comes with a terminal such as a mobile phone, a landline or a computer.
  • the terminal such as the telephone collects the sound of the local end through the sound collection device in real time, and transmits it to the opposite end of the call through the communication line.
  • the sound collection device at the local end collects the input sound signal, it is not directly transmitted to the call. Instead, through the following steps S102 to S106, the input sound signal is echo canceled to improve the quality of the voice call.
  • S102 Perform adaptive filtering on the input sound signal to obtain a near-end speech estimation signal.
  • the adaptive filtering method After acquiring the input sound signal from the sound collection device, the acquired input sound signal is filtered to filter out the echo signal generated at the local end that interferes with the normal call, and to obtain the near-end voice estimation signal after the echo signal is filtered out.
  • the adaptive filtering method can use an adaptive echo canceller (ie, AEC) to filter the input sound signal to filter out the near-end speech estimation signal.
  • AEC adaptive echo canceller
  • S103 Determine the current utterance state according to the near-end speech estimation signal.
  • the utterance state can include different states such as far-end utterance only, double-end utterance, and near-end utterance only.
  • the utterance state corresponds to different processing methods for the obtained near-end speech estimation signal, which can be set according to needs.
  • the vocal state of is not limited to the examples mentioned above.
  • the current utterance state is to determine the real-time utterance state of the near-end speech estimation signal obtained this time to determine its real-time corresponding utterance state.
  • the corresponding utterance state can be determined according to the waveform, channel and other attributes of the speech signal.
  • S104 Obtain a preset mapping relationship between the utterance state and the processing mode, and obtain the processing mode corresponding to the current utterance state according to the mapping relationship.
  • the processing method is a corresponding processing method for the near-end speech estimation signal of each utterance state, and may include processing methods such as setting the near-end speech estimation signal to zero (0), fully retaining or retaining part, and so on.
  • the mapping relationship between the utterance state and the processing mode can be set in advance. After the current utterance state is determined, the corresponding processing mode can be automatically obtained according to the mapping relationship.
  • S105 Process the near-end speech estimation signal according to the processing manner.
  • the near-end speech estimation signal is processed according to this processing mode.
  • S106 Output the processed near-end speech estimation signal to obtain an output signal.
  • the processed near-end voice estimation signal can correctly reflect the call information of the local end, and this output signal can be transmitted to the call peer through the communication link.
  • the input sound signal in a voice call such as a telephone
  • it is different from the direct transmission to the opposite device in the existing communication scheme or the transmission to the opposite device with only adaptive echo cancellation.
  • Different processing methods can be customized according to the different sounding states of the input sound signal, and the interference or echo in the input sound signal can be accurately filtered by combining the characteristics of double-ended sounding.
  • the call quality can be significantly improved.
  • Figure 2 provides a schematic diagram of the application of an echo cancellation method based on double-ended utterance detection; in the application scenario shown in Figure 2, the call object includes a far-end device 200 and a near-end device 210, where the far The end device 200 includes a far-end microphone 201 and a far-end speaker 202, and the near-end device 210 includes a near-end speaker 203 and a near-end microphone 204.
  • the far-end microphone 201 sends the downlink signal S1 to the near-end speaker 203
  • the direct echo S2 is the sound signal that is emitted by the near-end speaker 203 and is directly picked up by the near-end microphone 204
  • the indirect echo S3 is the sound signal from the near-end speaker.
  • 203 emits a sound signal that is reflected by the environment and indirectly picked up by the near-end microphone 204. While picking up the echoes (direct echo S2 and indirect echo S3), a person (not shown) sends a voice to the near-end microphone 204 (marked "voice" in the figure), and the near-end microphone 204 picks up the voice and generates an uplink signal S4 is sent to the remote speaker 202 to be played out.
  • the echo cancellation method based on double-ended voice detection in FIG. 1 can be applied to the near-end microphone 204 side in FIG. 2 where the near-end microphone 204 obtains the input sound signal to be sent to the far-end device 200 (that is, according to the voice in FIG. 2 Before the obtained sound signal), the input sound signal is processed by the echo cancellation method in FIG. 1 first.
  • Step S103 in FIG. 1 determines the current utterance state according to the near-end speech estimation signal, which may specifically include steps S301 to S303 in FIG. 3.
  • S301 Calculate the average value of the double-ended utterance state statistics of the current frame in the input sound signal according to the input sound signal and the near-end speech estimation signal.
  • the double-ended utterance state statistics of the current frame are based on the current frame in the input sound signal as the reference point, and the input sound signal and the near-end speech estimation signal before the reference point are respectively sampled, and the input sound signal and the near-end speech estimation signal are respectively sampled. Signals are compared, calculated, and used to reflect the current sounding state of the input sound signal.
  • the average value is the average value of the double-ended voice state statistics at several sampling points.
  • the average value of the double-ended utterance state statistics of the current frame may be obtained by inputting the input sound signal and the near-end speech estimation signal into the double-ended utterance detector.
  • S302 Acquire a dual-talk judgment threshold corresponding to the current frame, where the dual-talk judgment threshold is obtained according to the signal-to-return ratio of the input sound signal and the near-end interference signal.
  • the signal-to-return ratio of the input sound signal is the energy ratio of the signal and the echo in the input sound signal, and the signal-to-return ratio of the input sound signal can be calculated to obtain the signal-to-return ratio.
  • the near-end interference signal is the interference signal generated by the sound generated by the same-end sounding device corresponding to the sound collecting device on the reception of the microphone, and can be obtained from the sounding device corresponding to the sound collecting device.
  • the sound-producing device can be a device such as a speaker corresponding to the local microphone in telephone communication.
  • the dual-talk judgment threshold is the threshold value used to determine the utterance state corresponding to the average of the double-ended utterance state statistics of the current frame. Set multiple thresholds of the utterance state for the average value of the double-ended utterance state statistics, that is, dual-talk judgment Threshold.
  • the dual-talk judgment threshold is set based on two factors: the signal-to-return ratio of the input sound signal and the near-end interference signal.
  • S303 Determine the current utterance state according to the magnitude relationship between the average value of the double-ended utterance state statistics of the current frame and the double-talk determination threshold.
  • step S302 According to the relationship between the average value of the double-ended utterance state statistics of the current frame in the input sound signal and the double-talk judgment threshold obtained in step S302, it is determined which utterance state the average value of the double-ended utterance state statistics of the current frame is in. Within the threshold interval to determine the current vocalization state.
  • the real-time sounding state judgment is performed on each frame of the input sound signal to realize real-time update of the processing method of the near-end speech estimation signal, so that the input sound signal can be accurately and completely echo canceled. Ensure the stability of the call process.
  • step S301 the calculation method of the average value of the double-ended utterance state statistics of the current frame in the input sound signal can be calculated according to the following formula:
  • Step S302 in FIG. 3 obtains the dual-talk judgment threshold corresponding to the current frame.
  • the dual-talk judgment threshold is based on the signal-back ratio and near-end interference of the input sound signal.
  • Obtaining the signal may include steps S401 to S403 in Fig. 4, where:
  • S401 Estimate the signal-to-return ratio of the input sound signal in real time to obtain an average signal-to-return ratio of the current frame in the input sound signal.
  • S402 Acquire multiple preset thresholds of the response ratio, and construct multiple intervals of the ratio of the response ratio according to the multiple thresholds.
  • the preset multiple thresholds are values obtained through experience or extreme technical personnel.
  • the boundary values of multiple thresholds can be generated based on multiple thresholds to define multiple thresholds.
  • the corresponding dual-speaking judgment threshold is set for each response ratio interval.
  • S403 Determine a signal-to-return ratio interval to which the average return ratio of the current frame belongs, and obtain a dual-speaking judgment threshold corresponding to the signal-to-return ratio interval as the dual-speaking judgment threshold of the current frame.
  • the signal-to-return ratio of the input sound signal with the near-end interference signal as the echo source is calculated in real time by sampling.
  • different dual-talk judgments are set Threshold, more accurately determine the current sounding state, and improve the accuracy of echo cancellation for the input sound signal.
  • the calculation method of the average response ratio of the current frame in step S401 in FIG. 4 is as follows:
  • the near-end interference signal is a sound signal generated by a sound-producing device at the same end as the sound collection device.
  • P m (k, n) represents the power of the input sound signal at the k-th frame and the n-th sample point
  • P x (k, n ) Represents the power of the near-end interference signal at the k-th frame and the n-th sample point
  • mean() represents the average value of the values in the brackets.
  • P m (k, n) and P x (k, n) are the power values of the sampling points obtained by sampling the input sound signal and the near-end interference signal respectively in frames.
  • the sampling process is: acquiring n sample points in the input sound signal and the near-end interference signal respectively, and the signal frame corresponding to each sample point is the k-th frame. Among them, n and k are variable count values.
  • Step S402 in FIG. 4 obtains multiple preset thresholds of the response ratio, and constructs multiple intervals of the response ratio according to the multiple thresholds, which may include: Two adjacent ones of the acquired multiple thresholds of the response ratio are used as the boundary value of the response ratio interval to obtain a plurality of ratio intervals.
  • the threshold value is used as the boundary value of a RL interval to obtain multiple RL interval.
  • the preset multiple thresholds of the return ratio are SER_thr_1, SER_thr_2, SER_thr_3,..., SER_thr_k, and the return ratio interval is formed by the thresholds.
  • the information response ratio interval can be expressed as: the information response ratio interval 501, the information response ratio interval 502,..., the information response ratio interval 50k, where k is a variable value, which represents the kth information response ratio interval 50k, according to K+1 thresholds of the response ratio can construct k response ratio intervals of 50k.
  • the corresponding dual-speaking judgment threshold for each response ratio interval, that is, the dual-speaking judgment threshold m1, the dual-speaking judgment threshold m2, ..., the dual-speaking judgment threshold mk in Fig. 5.
  • the corresponding dual-talk judgment threshold is obtained, that is, step S403.
  • the RR interval is automatically constructed based on the preset RR threshold value as the interval boundary value.
  • the utterance state includes two states: only the far-end utterance and not only the far-end utterance, and the preset mapping relationship between the utterance state and the processing mode includes: when the utterance state is only the far-end utterance When the near-end speech estimation signal is zeroed or suppressed to be inaudible; when the utterance state is not only the far-end utterance, the near-end speech estimation signal is retained.
  • two voice states can be set, namely, only the far-end voice and not only the far-end voice.
  • the near-end speech estimation signal needs to be zeroed or suppressed to be inaudible, that is, the near-end speech estimation signal is filtered out, and the mute signal is used as The transmission signal of the local end is transmitted to the opposite end device of the call.
  • the near-end voice estimation signal When it is determined based on the near-end voice estimation signal that the current utterance state is not only the far-end utterance, the near-end voice estimation signal needs to be retained, and the near-end voice estimation signal is transmitted to the peer device of the call as a transmission signal of the local end.
  • two utterance states are defined, and processing methods corresponding to the two utterance states are specified, which can basically meet the requirements of real-time echo cancellation in common voice calls.
  • the not only far-end utterance includes two states: near-end utterance only and double-ended utterance.
  • near-end sound-only means that the sound collection device only collects the transmission from the local end. Signals, but no near-end interference signal is collected; the double-ended sounding state means that the sound collection device collects both the local transmission signal and the near-end interference signal.
  • the processing method can be further specified for these two states. For example, for only the near-end voice, no processing is done and the voice signal is directly transmitted to the opposite end, and so on.
  • Step S102 in FIG. 1 performs adaptive filtering on the input sound signal to obtain a near-end speech estimation signal, which may specifically include two filtering operations, namely linear filtering and non-linear filtering. .
  • the input sound signal is processed by linear filtering in filters such as AEC to eliminate part of the echo.
  • the input sound signal still contains linear residual echo and nonlinear echo.
  • near-end utterance it also contains near-end speech.
  • Continuous non-linear processing and filtering of the sound signal containing residual echo can be used to achieve further echo suppression.
  • the adaptive filtering of the input sound signal includes two operations of linear filtering and non-linear filtering, which can further suppress the echo of the input sound signal.
  • the embodiment of the application also provides an echo cancellation device based on double-ended vocalization detection. Please refer to FIG. 6.
  • the device may include an input sound signal acquisition module 601, a filtering module 602, a sound state determination module 603, and a processing mode acquisition module 604. , Near-end processing module 605 and output module 606, where:
  • the input sound signal acquisition module 601 is used to acquire the input sound signal from the sound collection device.
  • the filtering module 602 is configured to perform adaptive filtering on the input sound signal to obtain a near-end speech estimation signal.
  • the utterance state determination module 603 is configured to determine the current utterance state according to the near-end speech estimation signal.
  • the processing mode obtaining module 604 is configured to obtain a preset mapping relationship between the utterance state and the processing mode, and obtain the processing mode corresponding to the current utterance state according to the mapping relationship.
  • the near-end processing module 605 is configured to process the near-end speech estimation signal according to the processing mode.
  • the output module 606 is configured to output the processed near-end speech estimation signal to obtain an output signal.
  • the utterance state determination module 603 may include:
  • a real-time utterance state acquisition unit configured to calculate the average value of the double-ended utterance state statistics of the current frame in the input sound signal according to the input sound signal and the near-end speech estimation signal;
  • a threshold obtaining unit configured to obtain a dual-talk judgment threshold corresponding to the current frame, the dual-talk judgment threshold being obtained according to the signal-to-return ratio of the input sound signal and the near-end interference signal;
  • the utterance state determination unit is configured to determine the current utterance state according to the magnitude relationship between the average value of the double-ended utterance state statistics of the current frame and the dual-talk determination threshold.
  • the threshold value acquisition unit includes:
  • the current response ratio obtaining subunit is used to estimate the signal response ratio of the input sound signal in real time to obtain the average signal response ratio of the current frame in the input sound signal;
  • a signal response ratio interval construction subunit for obtaining a plurality of preset signal response ratio thresholds, and constructing a plurality of signal response ratio intervals according to the plurality of signal response ratio thresholds;
  • the threshold judging subunit is used to judge the interval of the average response ratio of the current frame to which the average response ratio belongs, and obtain the dual-speaking judgment threshold corresponding to the said interval as the dual-speaking judgment threshold of the current frame.
  • the above-mentioned signal response ratio interval construction subunit is further used to use two adjacent ones of the obtained multiple signal response ratio threshold values as the boundary value of the signal response ratio interval to obtain multiple signal response ratios. Back to the interval.
  • the filtering module 602 in FIG. 6 is further configured to perform linear filtering and non-linear filtering on the input sound signal to obtain the near-end speech estimation signal.
  • the embodiment of the present application also provides an echo cancellation system based on double-ended vocalization detection, including a sound collection device, a same-end sounding device, and an echo cancellation device.
  • the echo cancellation device performs the double-ended-based echo cancellation system provided in FIGS. 1 to 5. The steps of the echo cancellation method for vocal detection.
  • Figure 7 is a schematic diagram of an echo cancellation system based on double-ended voice detection; the system includes a sound collection device 701, an echo cancellation device 702, and a same-end voice device 703.
  • the sound collection device 701 may be a microphone in telephone communication for collecting the input sound signal A1.
  • the same-end sounding device 703 may be a speaker connected to the same end as a microphone in telephone communication to generate a sound signal, but it may interfere with the input sound signal A1, so it is used as the interference sound signal A6.
  • the echo cancellation device 702 is a device for implementing the echo cancellation method based on double-ended vocalization detection in FIGS. 1 to 5 in this application.
  • the function of the echo cancellation device can be realized by means of entity or logic circuit, software programming, etc.
  • the echo cancellation device 702 may include a linear AEC filter 7021, an NLP filter 7022, a double-ended utterance detector 7023, a signal-to-return ratio estimator 7024, a threshold determiner 7025 and a processor 7026.
  • the echo cancellation device 702 processes the sound signals received from the sound collection device 701 and the same-end sound device 703 in the communication process as follows:
  • the input sound signal A1 is linearly filtered through the linear AEC filter 7021 to obtain the linearly filtered sound signal A2, and then the NLP filter is applied to A2.
  • Non-linear filtering obtains the near-end speech estimation signal A3, which is used as an input signal of the double-ended utterance detector 7023.
  • the input sound signal A1 is directly used as another input signal of the double-ended sounding detector.
  • the linear AEC filter 7021 uses the interference sound signal A6 as a filtering reference factor to linearly filter the input sound signal A1.
  • the input sound signal A1 is input to the echo ratio estimator 7024, the average echo ratio A4 of the current frame of the input sound signal is calculated in real time, and the average echo ratio A4 is transmitted to the threshold determiner 7025, which is based on the preset Multiple signal response ratio intervals constructed by multiple signal response ratio thresholds to determine the dual-talk judgment threshold A5 corresponding to the average return ratio of the current frame A4, and send the double-talk judgment threshold A5 to the double-ended utterance detector 7023 As the basis for judging the current utterance state.
  • the signal-to-return ratio estimator 7024 samples the input sound signal A1 and the interference sound signal A6, and calculates the average signal-to-return ratio A4 of the current frame according to the following formula:
  • the double-ended utterance detector 7023 acquires the first input signal (ie the near-end voice estimation signal A3), the second input signal (ie the input sound signal A1), and the dual-talk judgment threshold A5, and determines the current utterance in real time based on this information State A7.
  • the current utterance state is obtained based on the average of the double-ended utterance state statistics of the current frame.
  • the double-ended utterance detector 7023 samples the near-end speech estimation signal A3 and the input sound signal A1, and calculates the average value of the double-ended utterance state statistics of the current frame according to the following formula:
  • the double-ended utterance detector 7023 sends the obtained current utterance state A7 to the processor 7026, and the processor 7026 processes the near-end voice estimation signal A3 according to the current utterance state A7.
  • the processing method is: when the utterance state is only the far-end utterance, the near-end speech estimation signal A3 is zeroed or suppressed to inaudible; when the utterance state is not only the far-end utterance, the near-end speech estimation signal A3 is retained.
  • the processed near-end speech estimation signal is output to obtain an output signal A8, and the output signal A8 can be transmitted to the device of the communication opposite end via the communication link.
  • the above-mentioned echo cancellation system based on double-ended vocalization detection performs real-time detection based on the acoustic echo generated in the communication process, and eliminates it according to the detection result, so that the echo cancellation effect can be improved when the voice communication terminal is in the hands-free mode to improve the call quality.
  • the echo cancellation method, device and system based on double-ended utterance detection provided in the embodiments of the present application can distinguish between only far-end utterance and only near-end utterance or double-ended utterance in real time.
  • the time-domain output result is zeroed or suppressed to inaudible, so that the echo can be eliminated to the greatest extent while ensuring the duplex call performance, so as to improve the echo cancellation and duplex performance at the same time.
  • the purpose is to improve the duplex call experience of the hands-free voice communication terminal.

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Abstract

一种基于双端发声检测的回声消除方法、装置及系统，其中，所述方法包括：从声音采集设备获取输入声音信号；对所述输入声音信号进行自适应滤波，得到近端语音估计信号；根据所述近端语音估计信号判定当前的发声状态；获取预设的发声状态与处理方式之间的映射关系，根据所述映射关系获取所述当前的发声状态对应的处理方式；根据所述处理方式对所述近端语音估计信号进行处理；将处理后的近端语音估计信号输出，得到所述输出信号。通过此方法，能够更好地消除回声，提升免提语音通信终端的双工通话体验。

Description

基于双端发声检测的回声消除方法、装置及系统
本申请要求于2019年12月13日提交中国专利局、申请号为201911284296.3、发明名称为“基于双端发声检测的回声消除方法、装置及系统”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及语音通讯领域，具体地涉及一种基于双端发声检测的回声消除方法、装置及系统。
背景技术
在电话终端中，声学回声是由于扬声器和终端麦克风之间的耦合，导致电话的麦克风不仅包含有用的语音信号，而且还包含回声。如果不对麦克风信号进行处理，则回声信号及近端语音信号会被传输到远端扬声器播放出来，远端通话者就会听到自己延迟后的声音，它会使人感到不舒服，从而影响通话的效果。当回声较大时，通话甚至无法正常进行。因此，必须采取有效措施来抑制回声，消除其影响，才能提高语音通信质量。
例如，在电话会议、免提电话等系统中，都不同程度的存在声学回声现象。回声消除从贝尔发明电话开始就成为工程上需要解决的问题。近年来，随着信息技术的飞速发展，通信方式和应用场景日趋多样化，通信终端日趋小型化，使得扬声器和麦克风的耦合越来越强，回声信道越来越复杂多变，这为语音通信中的声学回声消除带来了极大的挑战。
声学回声一般产生于免提通信系统中，是受声波传播影响的回声 产生方式，一般情况下可以分为两种情况：直接回声和间接回声。直接回声是指扬声器播放出来的声音未经任何反射沿路径直接进入麦克风被拾回，这种回声延迟时间最短，且与远端说话者的语音能量、扬声器与话筒之间的距离、角度、扬声器的播放音量及话筒的拾取灵敏度等因素有关。间接回声是指扬声器播放的声音经不同的路径一次或多次反射后进入麦克风所产生的回声集合，这种回声的特征是延迟时问长，延迟抖动大，回声音量受环境影响大。
现有技术中通常使用自适应回声消除器(Acoustic Echo Canceller，简称AEC)来消除回声。AEC的基本原理可以概括为自适应地估计回声，并从麦克风拾取的信号中减去该估计回声。在电话电路中，无论距离有多远，AEC可以使通话者之间免受回声影响；在免提电话中，AEC可以使回声最小化。当不存在近端声音时，AEC的回声消除效果能够满足当前需求；然而，当存在明显的近端声音时，基于现有各种自适应滤波算法的AEC的性能将发生恶化，甚至不能保证自适应滤波算法的收敛。这就是回声消除在实际应用中的必须解决的关键问题，通常称为双端发声(Double-talk，简称DT)问题。为了降低或避免双端发声对AEC性能的影响，可以使用双端发声检测器(Double-talk detector，简称DTD)，DTD的典型应用就是在双端讲话时段冻结AEC的更新，防止自适应滤波算法发散。
DTD是基于双端发声检测算法工作的。双端发声检测算法具体可以包括基于能量的双端发声检测算法、基于信号的相关特性的双端发声检测算法和基于谱特征的双端发声检测算法等。这些双端发声检测算法都依赖于固定阈值的选取，通过将计算的统计量与该阈值进行比较来判断发声状态。然而，由于实际信道以及通话情况的多变性，固定阈值法无法准确的检测双端发声状态。这不仅影响回声消除的鲁棒性，而且会在进行后续处理时产生严重的切音现象，即传输到远端用户的声音会发生断续。
在免提通话设备中主要的影响因素是麦克风接收信号的信回比， 即麦克风接收的近端语音与其接收的来自扬声器的回声信号的幅度(功率)比。相比于手持通话，免提通话时麦克风的信回比通常较低，且麦克风与近端讲话者的距离、近端讲话者音量、回声大小等都会令信回比发生变化，这使得传统的基于固定阈值的双端发声检测算法往往失效，难以平衡免提通话下的双工和去回声性能。
综上，现有技术中的回声消除技术，对于双端发声问题，尤其是免提通话、电话会议中的双端发声问题无法准确滤除其中的回声干扰，通话质量易受影响。
发明内容
本申请解决的技术问题是如何更好地消除回声，提升免提语音通信终端的双工通话体验。
为解决上述技术问题，本申请实施例提供一种基于双端发声检测的回声消除方法、装置及系统，其中，基于双端发声检测的回声消除方法可以包括：从声音采集设备获取输入声音信号；对所述输入声音信号进行自适应滤波，得到近端语音估计信号；根据所述近端语音估计信号判定当前的发声状态；获取预设的发声状态与处理方式之间的映射关系，根据所述映射关系获取所述当前的发声状态对应的处理方式；根据所述处理方式对所述近端语音估计信号进行处理；将处理后的近端语音估计信号输出，得到输出信号。
可选的，所述根据所述近端语音估计信号判定当前的发声状态，包括：根据所述输入声音信号和所述近端语音估计信号计算所述输入声音信号中当前帧的双端发声状态统计量的平均值；获取所述当前帧对应的双讲判断阈值，所述双讲判断阈值根据所述输入声音信号的信回比和近端干扰信号得到；根据所述当前帧的双端发声状态统计量的平均值与双讲判断阈值的大小关系，判定当前的发声状态。
可选的，所述根据所述输入声音信号和所述近端语音估计信号计 算所述输入声音信号中当前帧的双端发声状态统计量的平均值，包括：根据下述公式计算所述当前帧的双端发声状态统计量的平均值：；其中，为当前帧的双端发声状态统计量的平均值，表示近端语音估计信号在第k帧、第n个样本点的功率，表示所述输入声音信号在第k帧、第n个样本点的功率，表示取括号内数值的平均值。
可选的，所述获取所述当前帧对应的双讲判断阈值，所述双讲判断阈值根据所述输入声音信号的信回比和近端干扰信号得到，包括：实时估计所述输入声音信号的信回比，以得到所述输入声音信号中当前帧的平均信回比；获取预设的多个信回比阈值，并根据所述多个信回比阈值构建多个信回比区间；判断所述当前帧的平均信回比所属的信回比区间，并获取所述的信回比区间对应的双讲判断阈值作为所述当前帧的双讲判断阈值。
可选的，所述实时估计所述输入声音信号的信回比，以得到所述输入声音信号中当前帧的平均信回比，包括：获取近端干扰信号，所述近端干扰信号为与所述声音采集设备的同端发声设备产生的声音信号；根据下述公式计算所述输入声音信号中当前帧的平均信回比；；其中，表示估计得到的第k帧的平均信回比，其单位为dB，表示所述输入声音信号在第k帧、第n个样本点的功率，表示所述近端干扰信号在第k帧、第n个样本点的功率，表示取括号内数值的平均值。
可选的，所述获取预设的多个信回比阈值，并根据所述多个信回比阈值构建多个信回比区间，包括：将获取的所述多个信回比阈值中相邻的两个作为所述信回比区间的边界值，得到多个信回比区间。
可选的，所述发声状态包括仅远端发声和非仅远端发声两种状态，所述预设的发声状态与处理方式之间的映射关系包括：当发声状态为仅远端发声时，对所述近端语音估计信号作置零处理或抑制至不可闻；当发声状态判断为非仅远端发声时，保留所述近端语音估计信 号。
可选的，所述非仅远端发声包括仅近端发声和双端发声两种状态。
可选的，所述对所述输入声音信号进行自适应滤波，得到近端语音估计信号，包括：分别对所述输入声音信号进行线性滤波和非线性滤波，得到所述近端语音估计信号。
本申请实施例还提供一种基于双端发声检测的回声消除装置，所述装置包括：输入声音信号获取模块，用于从声音采集设备获取输入声音信号；滤波模块，用于对所述输入声音信号进行自适应滤波，得到近端语音估计信号；当前的发声状态判定模块，用于根据所述近端语音估计信号判定当前的发声状态；处理方式获取模块，用于获取预设的发声状态与处理方式之间的映射关系，根据所述映射关系获取所述当前的发声状态对应的处理方式；近端处理模块，用于根据所述处理方式对所述近端语音估计信号进行处理；输出模块，用于将处理后的近端语音估计信号输出得到输出信号。
本申请实施例还提供一种基于双端发声检测的回声消除系统，包括声音采集设备、同端发声设备和回声消除设备，所述回声消除设备执行上述任一项所述方法的步骤。
与现有技术相比，本申请实施例的技术方案具有以下有益效果：
本申请实施例中提供一种基于双端发声检测的回声消除方法，所述方法包括：从声音采集设备获取输入声音信号；对所述输入声音信号进行自适应滤波，得到近端语音估计信号；根据所述近端语音估计信号判定当前的发声状态；获取预设的发声状态与处理方式之间的映射关系，根据所述映射关系获取所述当前的发声状态对应的处理方式；根据所述处理方式对所述近端语音估计信号进行处理；将处理后的近端语音估计信号输出，得到输出信号。较之现有技术，对于电话等语音通话中的输入声音信号，区别于现有通讯方案中直接传输给对 端设备或者只做自适应回声消除即传输给对端设备，本方法中的技术方案，根据输入声音信号对应的不同发声状态定制不同的处理方式，以结合双端发声的特性对输入声音信号中的回声进行精准滤除。尤其是对于免提通话、语音会议等受双端发声干扰影响较大的通话系统中，能够显著提高通话质量。
进一步地，对输入声音信号中的各帧进行实时的发声状态判断，以实现实时更新对近端语音估计信号的处理方式，使得能够准确地对输入声音信号完整、准确地进行回声消除，保证通话过程的稳定。
进一步地，以采样的方式实时计算以近端干扰信号为回声源、输入声音信号的信回比，在近端干扰信号对输入声音信号的影响程度不同时，设定不同的双讲判断阈值，更加准确地判定当前的发声状态，提高对输入声音信号进行回声消除的准确性。
进一步地，定义了两种发声状态，并规定两种发声状态对应的处理方式，可基本满足常见的语音通话中实时回声消除的要求。
进一步地，对输入声音信号的自适应滤波包含线性滤波和非线性滤波两个操作，能够进一步对输入声音信号进行回声抑制。
本申请实施例提供的基于双端发声检测的回声消除系统，可根据通信过程中产生的声学回声进行实时检测、并根据检测结果予以消除，从而能够在语音通信终端处于免提模式下提高回声的消除效果，以提升通话质量。尤其针对免提语音通信终端，本申请实施例中提供的基于双端发声检测的回声消除方法、装置及系统，能够将仅远端发声和仅近端发声或双端发声的情况进行实时区分。当判断为仅远端发声时对时域输出结果作置零处理或抑制至不可闻，从而在保证双工通话性能的同时对回声作最大程度的消除，达到同时提高回声消除和双工性能的目的，提升免提语音通信终端的双工通话体验。
附图说明
图1是本申请实施例的一种基于双端发声检测的回声消除方法的流程示意图；
图2是本申请实施例的一种基于双端发声检测的回声消除方法的应用示意图；
图3是本申请一实施例中图1的步骤S103的流程示意图；
图4是本申请一实施例中图3中步骤S302的流程示意图；
图5是本申请实施例的一种信回比区间的示意图；
图6是本申请实施例的一种基于双端发声检测的回声消除装置的结构示意图；
图7是本申请实施例的一种基于双端发声检测的回声消除系统的结构示意图。
具体实施方式
如背景技术所言，现有技术中的回声消除技术，对于双端发声问题，尤其是免提通话、电话会议中的双端发声问题无法准确滤除其中的回声干扰，通话质量易受影响。
为解决上述技术问题，本申请实施例提供一种基于双端发声检测的回声消除方法，所述方法包括：从声音采集设备获取输入声音信号；对所述输入声音信号进行自适应滤波，得到近端语音估计信号；根据所述近端语音估计信号判定当前的发声状态；获取预设的发声状态与处理方式之间的映射关系，根据所述映射关系获取所述当前的发声状态对应的处理方式；根据处理方式对所述近端语音估计信号进行处理；将处理后的近端语音估计信号输出，得到输出信号。
采用本实施例所述方案的能够滤除双端发声中的干扰信号，显著提高通话质量。
具体请参见图1，图1提供了一种基于双端发声检测的回声消除 方法的流程示意图；该方法具体可以包括以下步骤：
S101，从声音采集设备获取输入声音信号。
输入声音信号是声音采集设备采集到的声音信号。其中声音采集设备可以为麦克风等设备，对于电话或者类电话形式的通话中，为手机、座机或电脑等终端自带的声音采集设备。
在电话通讯过程中，电话等终端实时通过声音采集设备采集本端的声音，并将其通过通信线路传输到通话的对端，在本端的声音采集设备采集到输入声音信号后，不直接传输给通话的对端，而是通过下述步骤S102至S106的步骤，对输入声音信号进行回声消除，以提高语音通话的质量。
S102，对所述输入声音信号进行自适应滤波，得到近端语音估计信号。
从声音采集设备获取输入声音信号后，对获取的输入声音信号进行滤波，以过滤掉本端产生的、干扰正常通话的回声信号，并获取滤除回声信号后的近端语音估计信号。其中，自适应滤波的方法，可以采用自适应回声消除器(即AEC)对输入声音信号进行滤波，过滤出近端语音估计信号。
S103，根据所述近端语音估计信号判定当前的发声状态。
其中，发声状态可以包括仅远端发声、双端发声和仅近端发声等等不同的状态，发声状态对应不同的对获取的近端语音估计信号的处理方式，可根据需要设定多种不同的发声状态，不限于前述所举的例子。当前的发声状态即为对本次过滤得到的近端语音估计信号进行实时的发声状态判定，以确定其实时对应的发声状态。
在获取近端语音估计信号后，可根据该语音信号的波形、信道等属性判定其对应的发声状态。
S104，获取预设的发声状态与处理方式之间的映射关系，根据所 述映射关系获取所述当前的发声状态对应的处理方式。
处理方式是对各发声状态的近端语音估计信号进行对应处理方式，可以包括将近端语音估计信号置零(0)、完全保留或者保留部分等等处理方式。可通过预先设定发声状态与处理方式之间的映射关系，在判定当前的发声状态后，即可根据映射关系自动获取对应的处理方式。
S105，根据所述处理方式对所述近端语音估计信号进行处理。
在步骤S104中获取当前的发声状态对应的处理方式后，即根据此处理方式对述近端语音估计信号进行处理。
S106，将处理后的近端语音估计信号输出，得到输出信号。
处理后的近端语音估计信号即可正确反映本端的通话信息，可将此输出信号通过通信链路传输给通话对端。
通过上述实施例中的方法，对于电话等语音通话中的输入声音信号，区别于现有通讯方案中直接传输给对端设备或者只做自适应回声消除即传输给对端设备，本实施例中根据输入声音信号对应的不同发声状态定制不同的处理方式，以结合双端发声的特性对输入声音信号中的干扰或回声进行精准滤除。尤其是对于免提通话、语音会议等受双端发声干扰影响较大的通话系统中，能够显著提高通话质量。
请参见图2，图2提供了一种基于双端发声检测的回声消除方法的应用示意图；在图2示出的应用场景中，通话对象包含远端设备200和近端设备210，其中，远端设备200包括远端麦克风201和远端扬声器202，近端设备210包括近端扬声器203和近端麦克风204。
在通讯过程中，远端麦克风201将下行信号S1送至近端扬声器203，直接回声S2是由近端扬声器203发出而被近端麦克风204直接拾取的声音信号，间接回声S3是由近端扬声器203发出经环境反射而被近端麦克风204间接拾取的声音信号。在拾取回声(直接回声S2和间接回声S3)的同时，人(图未示)对近端麦克风204发出语 音(见图中标记的“语音”)，由近端麦克风204拾取语音且产生上行信号S4被发送到远端扬声器202播放出来。
图1中的基于双端发声检测的回声消除方法可应用于图2中的近端麦克风204侧，在近端麦克风204获取待发送给远端设备200的输入声音信号(即根据图2中语音所得到的声音信号)之前，先通过图1中的回声消除方法对输入声音信号进行处理。
在一个实施例中，请继续参见图1，图1中的步骤S103根据所述近端语音估计信号判定当前的发声状态，具体可以包括图3中的步骤S301至S303：
S301，根据所述输入声音信号和所述近端语音估计信号计算所述输入声音信号中当前帧的双端发声状态统计量的平均值。
当前帧的双端发声状态统计量为以输入声音信号中的当前帧作为参考点，对参考点之前的输入声音信号和近端语音估计信号分别进行采样，通过对输入声音信号和近端语音估计信号进行对比、计算得出的、用于反映输入声音信号中当前的发声状态的数值。其平均值即为取双端发声状态统计量在若干个采样点的平均值。当前帧的双端发声状态统计量的平均值可以是将输入声音信号和近端语音估计信号输入双端发声检测器得到。
S302，获取所述当前帧对应的双讲判断阈值，所述双讲判断阈值根据所述输入声音信号的信回比和近端干扰信号得到。
其中，输入声音信号的信回比为输入声音信号中的信号和回声的能量比，可对输入声音信号进行信回比计算，以求得其信回比。
近端干扰信号是与声音采集设备对应的同端发声设备产生的声音对麦克风的接收产生的干扰信号，可从与声音采集设备相对应的发声设备获取。发声设备可以为在电话通信中本端麦克风对应的扬声器等设备。
双讲判断阈值为用于判定当前帧的双端发声状态统计量的平均 值对应的发声状态的阈值，对双端发声状态统计量的平均值设定多个发声状态的阈值，即双讲判断阈值。此双讲判断阈值为基于输入声音信号的信回比和近端干扰信号两个因素进行设定。
S303，根据所述当前帧的双端发声状态统计量的平均值与双讲判断阈值的大小关系，判定当前的发声状态。
根据输入声音信号中当前帧的双端发声状态统计量的平均值和步骤S302中得到的双讲判断阈值的大小关系，来判定当前帧的双端发声状态统计量的平均值处于哪一发声状态的阈值区间内，从而判定当前的发声状态。
本实施例中，对输入声音信号中的各帧进行实时的发声状态判断，以实现实时更新对近端语音估计信号的处理方式，使得能够准确地对输入声音信号完整、准确地进行回声消除，保证通话过程的稳定。
在一个实施例中，请继续参见图3，步骤S301中输入声音信号中当前帧的双端发声状态统计量的平均值的计算方式可以根据以下公式计算得到：
Figure PCTCN2020114168-appb-000001
其中，
Figure PCTCN2020114168-appb-000002
为当前帧的双端发声状态统计量的平均值，P S(k,n)表示近端语音估计信号在第k帧、第n个样本点的功率，P m(k,n)表示所述输入声音信号在第k帧、第n个样本点的功率，mean()表示取括号内数值的平均值。
在一个实施例中，请继续参见图3，图3中的步骤S302获取所述当前帧对应的双讲判断阈值，所述双讲判断阈值根据所述输入声音信号的信回比和近端干扰信号得到，可以包括图4中的步骤S401至S403，其中：
S401，实时估计所述输入声音信号的信回比，以得到所述输入声音信号中当前帧的平均信回比。
将输入声音信号传输到信回比计算器，以实时获取输入声音信号的信回比，并以当前帧作为参考点，计算在参考点之前的输入声音信号中近端干扰信号对其影响的量化数值，并对数值求平均值，得到当前帧的平均信回比。
S402，获取预设的多个信回比阈值，并根据所述多个信回比阈值构建多个信回比区间。
预设的多个信回比阈值是通过经验或者技术人员极端得到的数值，可根据多个信回比阈值生成多个信回比区间的边界值，以限定多个信回比区间。每个信回比区间设定对应的双讲判断阈值。
S403，判断所述当前帧的平均信回比所属的信回比区间，并获取所述的信回比区间对应的双讲判断阈值作为所述当前帧的双讲判断阈值。
判定得到的输入声音信号中当前帧的平均信回比所属的信回比区间，并将该信回比区间设定对应的双讲判断阈值作为当前帧的双讲判断阈值，执行上述图3中步骤S302的操作。
本实施例中，以采样的方式实时计算以近端干扰信号为回声源、输入声音信号的信回比，在近端干扰信号对输入声音信号的影响程度不同时，设定不同的双讲判断阈值，更加准确地判定当前的发声状态，提高对输入声音信号进行回声消除的准确性。
可选的，图4中的步骤S401中当前帧的平均信回比计算方式如下：
获取近端干扰信号，所述近端干扰信号为与所述声音采集设备的同端发声设备产生的声音信号。
根据下述公式计算所述输入声音信号中当前帧的平均信回比；
Figure PCTCN2020114168-appb-000003
其中，
Figure PCTCN2020114168-appb-000004
表示估计得到的第k帧的平均信回比，其单位为dB， P m(k,n)表示所述输入声音信号在第k帧、第n个样本点的功率，P x(k,n)表示所述近端干扰信号在第k帧、第n个样本点的功率，mean()表示取括号内数值的平均值。
P m(k,n)和P x(k,n)是对输入声音信号和近端干扰信号分别按帧进行采样、得到的采样点的功率值。采样过程为：各自获取输入声音信号和近端干扰信号中的n个样本点，每一样本点对应的信号帧为第k帧。其中，n和k为可变的计数数值。
在一个实施例中，请继续参见图4，图4中的步骤S402获取预设的多个信回比阈值，并根据所述多个信回比阈值构建多个信回比区间，可以包括：将获取的所述多个信回比阈值中相邻的两个作为所述信回比区间的边界值，得到多个信回比区间。
可存储预设的多个信回比阈值，当需构建信回比区间时，从存储区域获取存储的信回比阈值，将其按照数值大小的顺序进行排序，以排序后相邻的两个阈值作为一个信回比区间的边界值，以得到多个信回比区间。
例如，预设的多个信回比阈值为SER_thr_1，SER_thr_2，SER_thr_3，…，SER_thr_k，由该信回比阈值构成信回比区间请参见图5，图5提供了一实施例中信回比区间的示意图。
其中，信回比区间可表示为：信回比区间501，信回比区间502，…，信回比区间50k，其中k为一可变的数值，表示第k个信回比区间50k，根据k+1个信回比阈值可构建k个信回比区间50k。
继续地，为每一信回比区间设定对应的双讲判断阈值，即图5中的双讲判断阈值m1，双讲判断阈值m2，…，双讲判断阈值mk。判定当前帧的平均信回比所属的信回比区间后，即获取对应的双讲判断阈值，即步骤S403。
本实施例中，信回比区间是以预设的信回比阈值为区间边界值自动构建的。
在一个实施例中，所述发声状态包括仅远端发声和非仅远端发声两种状态，所述预设的发声状态与处理方式之间的映射关系包括：当发声状态为仅远端发声时，对所述近端语音估计信号作置零处理或抑制至不可闻；当发声状态为非仅远端发声时，保留所述近端语音估计信号。
可根据近端语音估计信号对于实际通话的影响，来设置两种发声状态，即仅远端发声和非仅远端发声。当根据近端语音估计信号判定当前的发声状态为仅远端发声时，则需将近端语音估计信号作置零处理或抑制至不可闻，即滤除近端语音估计信号，将静音信号作为本端的传输信号传输到通话的对端设备。当根据近端语音估计信号判定当前的发声状态为非仅远端发声时，则需保留近端语音估计信号，并将近端语音估计信号作为本端的传输信号传输到通话的对端设备。
本实施例中，定义了两种发声状态，并规定两种发声状态对应的处理方式，可基本满足常见的语音通话中实时回声消除的要求。
可选的，所述非仅远端发声包括仅近端发声和双端发声两种状态。
可继续对上述的非仅远端发声这一发声状态进行细化分析，将其分为仅近端发声和双端发声两种状态，仅近端发声即为声音采集设备仅采集到本端的传输信号，而未采集到近端干扰信号；双端发声状态即声音采集设备既采集到本端的传输信号，又采集到近端干扰信号。可针对这两个状态进一步规定处理方式。如，对于仅近端发声则不做处理而直接向对端传输声音信号等等。
在一个实施例中请继续参见图1，图1中的步骤S102对所述输入声音信号进行自适应滤波，得到近端语音估计信号，具体可以包括两次滤波操作，即线性滤波和非线性滤波。
将输入声音信号经AEC等滤波器件中的线性滤波处理，以消除部分回声。然而输入声音信号经线性滤波后，仍包含线性残余回声和 非线性回声，在有近端发声的情况下，还会包含近端语音。对包含残余回声的声音信号继续进行非线性处理滤波可用于实现进一步的回声抑制。
本实施例中，对输入声音信号的自适应滤波包含线性滤波和非线性滤波两个操作，能够进一步对输入声音信号进行回声抑制。
本申请实施例还提供了一种基于双端发声检测的回声消除装置，请参见图6，该装置可包含输入声音信号获取模块601、滤波模块602、发声状态判定模块603、处理方式获取模块604、近端处理模块605和输出模块606，其中：
输入声音信号获取模块601，用于从声音采集设备获取输入声音信号。
滤波模块602，用于对所述输入声音信号进行自适应滤波，得到近端语音估计信号。
发声状态判定模块603，用于根据所述近端语音估计信号判定当前的发声状态。
处理方式获取模块604，用于获取预设的发声状态与处理方式之间的映射关系，根据所述映射关系获取所述当前的发声状态对应的处理方式。
近端处理模块605，用于根据所述处理方式对所述近端语音估计信号进行处理。
输出模块606，用于将处理后的近端语音估计信号输出，得到输出信号。
在一个实施例中，发声状态判定模块603可以包括：
发声状态实时获取单元，用于根据所述输入声音信号和所述近端语音估计信号计算所述输入声音信号中当前帧的双端发声状态统计量的平均值；
阈值获取单元，用于获取所述当前帧对应的双讲判断阈值，所述双讲判断阈值根据所述输入声音信号的信回比和近端干扰信号得到；
发声状态判定单元，用于根据所述当前帧的双端发声状态统计量的平均值与双讲判断阈值的大小关系，判定当前的发声状态。
在一个实施例中，所述阈值获取单元，包括：
当前信回比获取子单元，用于实时估计所述输入声音信号的信回比，以得到所述输入声音信号中当前帧的平均信回比；
信回比区间构建子单元，用于获取预设的多个信回比阈值，并根据所述多个信回比阈值构建多个信回比区间；
阈值判断子单元，用于判断所述当前帧的平均信回比所属的信回比区间，并获取所述的信回比区间对应的双讲判断阈值作为所述当前帧的双讲判断阈值。
在一个实施例中，上述信回比区间构建子单元，还用于将获取的所述多个信回比阈值中相邻的两个作为所述信回比区间的边界值，得到多个信回比区间。
在一个实施例中，请继续参见图6，图6中的滤波模块602还用于，分别对所述输入声音信号进行线性滤波和非线性滤波，得到所述近端语音估计信号。
关于所述基于双端发声检测的回声消除装置的工作原理、工作方式的更多内容，可以参照上述图1至图5中的相关描述，这里不再赘述。
本申请实施例中还提供一种基于双端发声检测的回声消除系统，包括声音采集设备、同端发声设备和回声消除设备，所述回声消除设备执行图1至图5中提供的基于双端发声检测的回声消除方法的步骤。
请参见图7，图7为一种基于双端发声检测的回声消除系统的示 意图；该系统包括声音采集设备701、回声消除设备702和同端发声设备703。其中，声音采集设备701可以为电话通讯中的麦克风，用于采集输入声音信号A1。同端发声设备703可以为电话通讯中与麦克风同端连接的扬声器，用于产生声音信号，但其对于输入声音信号A1可能产生干扰，故将其作为干扰声音信号A6。回声消除设备702为本申请实现图1至图5中基于双端发声检测的回声消除方法的设备，可通过实体或者逻辑电路、以及软件编程等方式实现回声消除设备的功能。
可选的，如图7所示，回声消除设备702可以包括线性AEC滤波器7021、NLP滤波器7022、双端发声检测器7023、信回比估计器7024、阈值判断器7025以及处理器7026。
该回声消除设备702对于通讯过程中接收自声音采集设备701、同端发声设备703的声音信号的处理方式为：
从声音采集设备701中获取输入声音信号A1，对其进行回声消除，将输入声音信号A1经由线性AEC滤波器7021进行线性滤波，得到线性滤波后的声音信号A2，再经NLP滤波器对A2进行非线性滤波，得到近端语音估计信号A3，将其作为双端发声检测器7023的一路输入信号。将输入声音信号A1直接作为双端发声检测器的另一路输入信号。其中，线性AEC滤波器7021以干扰声音信号A6作为滤波参考因子对输入声音信号A1进行线性滤波。
另外，将输入声音信号A1输入信回比估计器7024，实时计算输入声音信号当前帧的平均信回比A4，并将平均信回比A4传输至阈值判断器7025，阈值判断器7025根据预设的多个信回比阈值所构建的多个信回比区间，以确定当前帧的平均信回比A4所对应的双讲判断阈值A5，将双讲判断阈值A5发送至双端发声检测器7023作为当前的发声状态判定的依据。其中，信回比估计器7024对输入声音信号A1和干扰声音信号A6进行采样，根据下列公式计算得到当前帧的平均信回比A4：
Figure PCTCN2020114168-appb-000005
其中，
Figure PCTCN2020114168-appb-000006
表示估计得到的第k帧的平均信回比，其单位为dB，P m(k,n)表示所述输入声音信号A1在第k帧、第n个样本点的功率，P x(k,n)表示近端干扰信号A6在第k帧、第n个样本点的功率，mean()表示取括号内数值的平均值。
双端发声检测器7023获取第一路输入信号(即近端语音估计信号A3)、第二路输入信号(即输入声音信号A1)以及双讲判断阈值A5，根据这些信息来实时判定当前的发声状态A7。当前的发声状态是基于当前帧的双端发声状态统计量的平均值得到的。双端发声检测器7023对近端语音估计信号A3和输入声音信号A1进行采样，根据下列公式计算得到当前帧的双端发声状态统计量的平均值：
Figure PCTCN2020114168-appb-000007
其中，
Figure PCTCN2020114168-appb-000008
为当前帧的双端发声状态统计量的平均值，P S(k,n)表示近端语音估计信号A3在第k帧、第n个样本点的功率，P m(k,n)表示所述输入声音信号A1在第k帧、第n个样本点的功率，mean()表示取括号内数值的平均值。
双端发声检测器7023将得到的当前的发声状态A7发送给处理器7026，处理器7026根据当前的发声状态A7对近端语音估计信号A3进行处理。处理方式为：当发声状态为仅远端发声时，对近端语音估计信号A3作置零处理或抑制至不可闻；当发声状态为非仅远端发声时，保留近端语音估计信号A3。将处理后的近端语音估计信号输出，得到输出信号A8，可将该输出信号A8经由通信链路传输至通信对端的设备。
请参见图2中的基于双端发声检测的回声消除方法的应用场景，可将图7中的系统应用到该场景中的近端设备侧，以消除图2中的直接回声S2、间接回声S3。
上述基于双端发声检测的回声消除系统，根据通信过程中产生的 声学回声进行实时检测、并根据检测结果予以消除，从而能够在语音通信终端处于免提模式下提高回声的消除效果，以提升通话质量。
尤其针对免提语音通信终端，本申请实施例中提供的基于双端发声检测的回声消除方法、装置及系统，能够将仅远端发声和仅近端发声或双端发声的情况进行实时区分。当判断为仅远端发声时对时域输出结果作置零处理或抑制至不可闻，从而在保证双工通话性能的同时对回声作最大程度的消除，达到同时提高回声消除和双工性能的目的，提升免提语音通信终端的双工通话体验。
虽然本申请披露如上，但本申请并非限定于此。任何本领域技术人员，在不脱离本申请的精神和范围内，均可作各种更动与修改，因此本申请的保护范围应当以权利要求所限定的范围为准。

Claims (11)

  1. 一种基于双端发声检测的回声消除方法，其特征在于，所述方法包括：
    从声音采集设备获取输入声音信号；
    对所述输入声音信号进行自适应滤波，得到近端语音估计信号；
    根据所述近端语音估计信号判定当前的发声状态；
    获取预设的发声状态与处理方式之间的映射关系，根据所述映射关系获取所述当前的发声状态对应的处理方式；
    根据所述处理方式对所述近端语音估计信号进行处理；
    将处理后的近端语音估计信号输出，得到输出信号。
  2. 根据权利要求1所述的方法，其特征在于，所述根据所述近端语音估计信号判定当前的发声状态，包括：
    根据所述输入声音信号和所述近端语音估计信号计算所述输入声音信号中当前帧的双端发声状态统计量的平均值；
    获取所述当前帧对应的双讲判断阈值，所述双讲判断阈值根据所述输入声音信号的信回比和近端干扰信号得到；
    根据所述当前帧的双端发声状态统计量的平均值与双讲判断阈值的大小关系，判定当前的发声状态。
  3. 根据权利要求2所述的方法，其特征在于，所述根据所述输入声音信号和所述近端语音估计信号计算所述输入声音信号中当前帧的双端发声状态统计量的平均值，包括：
    根据下述公式计算所述当前帧的双端发声状态统计量的平均值：
    Figure PCTCN2020114168-appb-100001
    其中，
    Figure PCTCN2020114168-appb-100002
    为当前帧的双端发声状态统计量的平均值，P S(k,n)表 示近端语音估计信号在第k帧、第n个样本点的功率，P m(k,n)表示所述输入声音信号在第k帧、第n个样本点的功率，mean()表示取括号内数值的平均值。
  4. 根据权利要求2所述的方法，其特征在于，所述获取所述当前帧对应的双讲判断阈值，所述双讲判断阈值根据所述输入声音信号的信回比和近端干扰信号得到，包括：
    实时估计所述输入声音信号的信回比，以得到所述输入声音信号中当前帧的平均信回比；
    获取预设的多个信回比阈值，并根据所述多个信回比阈值构建多个信回比区间；
    判断所述当前帧的平均信回比所属的信回比区间，并获取所述的信回比区间对应的双讲判断阈值作为所述当前帧的双讲判断阈值。
  5. 根据权利要求4所述的方法，其特征在于，所述实时估计所述输入声音信号的信回比，以得到所述输入声音信号中当前帧的平均信回比，包括：
    获取近端干扰信号，所述近端干扰信号为与所述声音采集设备的同端发声设备产生的声音信号；
    根据下述公式计算所述输入声音信号中当前帧的平均信回比；
    Figure PCTCN2020114168-appb-100003
    其中，
    Figure PCTCN2020114168-appb-100004
    表示估计得到的第k帧的平均信回比，其单位为dB，P m(k,n)表示所述输入声音信号在第k帧、第n个样本点的功率，P x(k,n)表示所述近端干扰信号在第k帧、第n个样本点的功率，mean()表示取括号内数值的平均值。
  6. 根据权利要求4所述的方法，其特征在于，所述获取预设的多个信回比阈值，并根据所述多个信回比阈值构建多个信回比区间， 包括：
    将获取的所述多个信回比阈值中相邻的两个作为所述信回比区间的边界值，得到多个信回比区间。
  7. 根据权利要求1所述的方法，其特征在于，所述发声状态包括仅远端发声和非仅远端发声两种状态，所述预设的发声状态与处理方式之间的映射关系包括：
    当发声状态为仅远端发声时，对所述近端语音估计信号作置零处理或抑制至不可闻；
    当发声状态为非仅远端发声时，保留所述近端语音估计信号。
  8. 根据权利要求7所述的方法，其特征在于，所述非仅远端发声包括仅近端发声和双端发声两种状态。
  9. 根据权利要求1所述的方法，其特征在于，所述对所述输入声音信号进行自适应滤波，得到近端语音估计信号，包括：
    分别对所述输入声音信号进行线性滤波和非线性滤波，得到所述近端语音估计信号。
  10. 一种基于双端发声检测的回声消除装置，其特征在于，所述装置包括：
    输入声音信号获取模块，用于从声音采集设备获取输入声音信号；
    滤波模块，用于对所述输入声音信号进行自适应滤波，得到近端语音估计信号；
    发声状态判定模块，用于根据所述近端语音估计信号判定当前的发声状态；
    处理方式获取模块，用于获取预设的发声状态与处理方式之间的映射关系，根据所述映射关系获取所述当前的发声状态对应的处理方式；
    近端处理模块，用于根据所述处理方式对所述近端语音估计信号进行处理；
    输出模块，用于将处理后的近端语音估计信号输出，得到输出信号。
  11. 一种基于双端发声检测的回声消除系统，包括声音采集设备、同端发声设备和回声消除设备，其特征在于，所述回声消除设备执行权利要求1至9任一项所述方法的步骤。
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115512691A (zh) * 2022-10-11 2022-12-23 四川虹微技术有限公司 一种人机连续对话中基于语义层面判断回声的方法
CN115706875A (zh) * 2021-08-07 2023-02-17 深圳方位通讯科技有限公司 对讲语音质量优化方法、装置、设备及存储介质

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110995951B (zh) * 2019-12-13 2021-09-03 展讯通信（上海）有限公司 基于双端发声检测的回声消除方法、装置及系统
CN111556210B (zh) * 2020-04-23 2021-10-22 深圳市未艾智能有限公司 通话语音处理方法与装置、终端设备和存储介质
CN113225442B (zh) * 2021-04-16 2022-09-02 杭州网易智企科技有限公司 一种消除回声的方法及装置
CN113241085B (zh) * 2021-04-29 2022-07-22 北京梧桐车联科技有限责任公司 回声消除方法、装置、设备及可读存储介质
CN113808609B (zh) * 2021-09-18 2024-07-19 展讯通信（上海）有限公司 回声检测方法及装置、计算机可读存储介质、终端设备
CN113936682A (zh) * 2021-11-30 2022-01-14 杭州网易智企科技有限公司 回声消除方法及装置、存储介质和电子设备

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101179294A (zh) * 2006-11-09 2008-05-14 爱普拉斯通信技术（北京）有限公司 自适应回声消除器及其回声消除方法
CN102655558A (zh) * 2012-05-21 2012-09-05 宁波工程学院 一种双端发音鲁棒结构及其消除声学回声的方法
US20120281603A1 (en) * 2011-05-06 2012-11-08 Futurewei Technologies, Inc. Transmit Phase Control for the Echo Cancel Based Full Duplex Transmission System
CN107635082A (zh) * 2016-07-18 2018-01-26 深圳市有信网络技术有限公司 一种双端发声端检测系统
CN110995951A (zh) * 2019-12-13 2020-04-10 展讯通信（上海）有限公司 基于双端发声检测的回声消除方法、装置及系统

Family Cites Families (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP3922997B2 (ja) * 2002-10-30 2007-05-30 沖電気工業株式会社 エコーキャンセラ
CN1925346A (zh) * 2006-09-05 2007-03-07 华为技术有限公司 一种回波抵消中双讲状态的检测方法
JP4411309B2 (ja) * 2006-09-21 2010-02-10 Ｏｋｉセミコンダクタ株式会社 ダブルトーク検出方法
US8345860B1 (en) * 2008-05-09 2013-01-01 Hellosoft India PVT. Ltd Method and system for detection of onset of near-end signal in an echo cancellation system
CN102160296B (zh) * 2009-01-20 2014-01-22 华为技术有限公司 双端通话检测方法及装置
CN101719969B (zh) * 2009-11-26 2013-10-02 美商威睿电通公司 判断双端对话的方法、系统以及消除回声的方法和系统
CN102377453B (zh) * 2010-08-06 2014-02-26 联芯科技有限公司 一种控制自适应滤波器更新的方法、装置及回声消除器
CN101917527B (zh) * 2010-09-02 2013-07-03 杭州华三通信技术有限公司 回声消除的方法和装置
CN102065190B (zh) * 2010-12-31 2013-08-28 杭州华三通信技术有限公司 一种回声消除方法及其装置
CN103179296B (zh) * 2011-12-26 2017-02-15 中兴通讯股份有限公司 一种回波抵消器及回波抵消方法
US9100466B2 (en) * 2013-05-13 2015-08-04 Intel IP Corporation Method for processing an audio signal and audio receiving circuit
CN104519212B (zh) * 2013-09-27 2017-06-20 华为技术有限公司 一种消除回声的方法及装置
US20160171988A1 (en) * 2014-12-15 2016-06-16 Wire Swiss Gmbh Delay estimation for echo cancellation using ultrasonic markers
CN106533500B (zh) * 2016-11-25 2019-11-12 上海伟世通汽车电子系统有限公司 一种优化回声消除器收敛特性的方法
CN108134863B (zh) * 2017-12-26 2020-06-19 中山大学花都产业科技研究院 一种基于双统计量的改进型双端检测装置及检测方法
CN108540680B (zh) * 2018-02-02 2021-03-02 广州视源电子科技股份有限公司 讲话状态的切换方法及装置、通话系统
CN108696648B (zh) * 2018-05-16 2021-08-24 上海小度技术有限公司 一种短时语音信号处理的方法、装置、设备及存储介质
CN109547655A (zh) * 2018-12-30 2019-03-29 广东大仓机器人科技有限公司 一种网络语音通话的回声消除处理的方法
CN110138990A (zh) * 2019-05-14 2019-08-16 浙江工业大学 一种消除移动设备VoIP电话回声的方法
CN110335618B (zh) * 2019-06-06 2021-07-30 福建星网智慧软件有限公司 一种改善非线性回声抑制的方法及计算机设备

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101179294A (zh) * 2006-11-09 2008-05-14 爱普拉斯通信技术（北京）有限公司 自适应回声消除器及其回声消除方法
US20120281603A1 (en) * 2011-05-06 2012-11-08 Futurewei Technologies, Inc. Transmit Phase Control for the Echo Cancel Based Full Duplex Transmission System
CN102655558A (zh) * 2012-05-21 2012-09-05 宁波工程学院 一种双端发音鲁棒结构及其消除声学回声的方法
CN107635082A (zh) * 2016-07-18 2018-01-26 深圳市有信网络技术有限公司 一种双端发声端检测系统
CN110995951A (zh) * 2019-12-13 2020-04-10 展讯通信（上海）有限公司 基于双端发声检测的回声消除方法、装置及系统

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115706875A (zh) * 2021-08-07 2023-02-17 深圳方位通讯科技有限公司 对讲语音质量优化方法、装置、设备及存储介质
CN115512691A (zh) * 2022-10-11 2022-12-23 四川虹微技术有限公司 一种人机连续对话中基于语义层面判断回声的方法

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