EP0110467B1 - Dispositif pour la détection des silences dans les signaux de paroles - Google Patents

Dispositif pour la détection des silences dans les signaux de paroles Download PDF

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Publication number
EP0110467B1
EP0110467B1 EP83201638A EP83201638A EP0110467B1 EP 0110467 B1 EP0110467 B1 EP 0110467B1 EP 83201638 A EP83201638 A EP 83201638A EP 83201638 A EP83201638 A EP 83201638A EP 0110467 B1 EP0110467 B1 EP 0110467B1
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value
short
arrangement
estimate
time mean
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German (de)
English (en)
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EP0110467A1 (fr
EP0110467B2 (fr
Inventor
Bernd Dipl.-Ing. Selbach
Peter Dr. Ing. Vary
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Philips Kommunikations Industrie AG
Koninklijke Philips NV
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Philips Kommunikations Industrie AG
Philips Gloeilampenfabrieken NV
Koninklijke Philips Electronics NV
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    • 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
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
    • G10L25/78—Detection of presence or absence of voice signals
    • G10L25/87—Detection of discrete points within a voice signal
    • 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
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
    • G10L25/78—Detection of presence or absence of voice signals
    • 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
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
    • G10L25/78—Detection of presence or absence of voice signals
    • G10L2025/783—Detection of presence or absence of voice signals based on threshold decision
    • G10L2025/786—Adaptive threshold

Definitions

  • the invention relates to an arrangement for recognizing speech pauses in a speech signal, according to the preamble of patent claim 1.
  • Such arrangements are e.g. the prerequisite for the suppression of interference signals when calling from an acoustically disturbed environment.
  • characteristic parameters of the interference signal are measured and used to filter out the interference as completely as possible from the signal to be transmitted using adaptive filters.
  • a circuit arrangement for recognizing speech pauses in a speech signal in which a short-term mean value is determined at certain clock instants of a clock.
  • the circuit arrangement known therefrom has a fixed threshold and two adaptively tracked thresholds, the sign of the respective slope in the speech signal being used in the tracking of the thresholds.
  • the adaptive noise thresholds are changed by constant amounts, so that these are not determined as a function of own values at previous clock instants.
  • Such a circuit arrangement is preferably used for the recognition of speech pauses in a speech signal, on which only weak interference signals are superimposed.
  • This break detection does not take into account, among other things, that z. B. unvoiced sounds lead to a drop in performance in the speech signal and the speech sections in question are therefore incorrectly regarded as speech pauses. Such mistakes in the known arrangement occur all the more, the more the speech signal is overlaid with interference signals.
  • the arrangement is also intended to enable speech pause recognition even if the average noise level changes only slowly.
  • kT o samples x (k) are obtained from the disturbed speech signal applied to a terminal E by an analog-to-digital converter A / D at sampling times, where k is a natural number and I / T o the sampling frequency represents.
  • the samples are passed on to an averager M.
  • the mean value generator M At all clock instants T (n) with the time interval mT o , the mean value generator M generates a so-called short-term mean value from the amounts of m consecutive samples.
  • the arithmetic mean of the amounts of the sampled values is used as the mean value, since the block expenditure is less than z. B. to form the square mean.
  • Each short-term mean value G (n) is approximately a measure of the average power of the disturbed speech signal over a period of approximately 100 ms. This specification and the sampling frequency also determine the number m of samples which are required to determine one of the short-term mean values G (n). Is z. B. sampled the disturbed speech signal at 10 kHz, m must be about 1000. Each of the quantities G (1), G (2) ... thus results from approximately a thousand consecutive samples.
  • the unit GL of FIG. 1 smoothes the sequence of the short-term mean values G (n). More about the purpose and manner of smoothing is given below.
  • block PA of FIG. 1 converts the short-term mean values into an estimated value P (n) for the average noise power, i.e. determined for the average power of the interference signal. More details about the estimate P (n) are also given below.
  • a comparator V in FIG. 1 compares a threshold S dependent on the estimated value P (n) with the smoothed short-term mean values GG (n). If the smoothed short-term mean value GG (n) is less than the threshold S, a signal is forwarded to a unit EN. Has the unit EN z. B. at two consecutive clock instants T (n-1) and T (n) receive such a signal, they can in turn detect the presence of a speech pause by means of their own signal at terminal A.
  • the diagram a) of Fig. 2 shows a possible output signal AM of the averager M, i.e. a possible sequence of the short-term mean values G (1), G (2) ...
  • the output signal AM is standardized so that its absolute maximum assumes the value 1.
  • the amplitude thresholds entered are the estimated value P (n) (lower threshold, shown in broken lines) and the threshold S (upper threshold, solid).
  • Diagram b) schematically shows the associated speech signal S with its true pauses P. If a pause determination were made due to the fact that the upper amplitude threshold was not reached in diagram a) - this pause determination is shown in diagram c) - a large number of wrong decisions would result, as a comparison of diagrams b) and c) shows.
  • a shift of the upper threshold downward would lead to the fact that the performance drops contained in diagram c), which are not based on language breaks, would not be displayed either, but the statement about the length of the breaks would then be significantly falsified.
  • a smoothing of the output signal AM is provided before the decision to pause, either with the aid of a linear digital filter, by means of which three successive short-term mean values G (n), G (n-1) and G (n- 2) a value GG (n) of the smoothed signal is obtained, or using a median filter.
  • FIG. 3 shows how the output signal of the mean value generator M looks after smoothing with a linear digital filter.
  • diagram b) the true speech sections and the real pauses of the speech signal are in turn plotted, and diagram c) shows the speech sections and speech pauses as they result analogously to diagram c) in FIG. 1. Due to the linear smoothing, the number of wrong decisions has decreased considerably, as the comparison of FIGS. 2 and 3 shows. Even with smoothing with a median filter, the number of incorrect decisions is reduced, as can be seen from diagram c) in FIG. 4.
  • a drop in performance can only be regarded as a speech pause if the upper amplitude threshold is fallen below twice in FIG. 2, 3 or 4.
  • the amplitude thresholds shown in FIGS. 2, 3 and 4 are - as already indicated above - determined by the unit PA in FIG. 1, namely that the estimated value P (n) of the noise power is initially determined for each time T (n).
  • This variable is intended to be an approximate measure of the average power of the interference signal, the averaging time being of the order of one second.
  • the arrangement according to the invention still delivers good results even if the above-mentioned average power of the interference signal changes only slowly , ie if it is to be regarded as stationary in time intervals of the size, one or two seconds.
  • the estimated value P (n) is a linear combination of the previous estimated value (P (n-1) and the short-term mean value G (n) according to the equation redefined.
  • the value of the constant a appearing in this equation is between zero and one.
  • a threshold D in terms of amount. Is z. B. K times the inequality in succession is satisfied, this fact is considered to be a longer speech pause and the new estimated value P (n) is determined according to the equation given above.
  • the threshold D is selected proportional to the short-term mean G (n) in order to arrive at the same statements if, for. B. the levels of all signals would be doubled.
  • the proportionality factor y and the number K are to be determined experimentally in such a way that as few incorrect decisions as possible are made by the arrangement. Typical values are
  • the constant c is to be chosen so that the estimation value reaches the modulation limit in one to two seconds with unimpeded enlargement. If, on the other hand, the already existing estimated value P (n-1) lies above the current short-term mean value G (n), the new estimated value P (n) is lowered compared to the existing one, specifically according to the equation which represents the new estimated value as a linear combination of the previous estimated value and the current short-term mean value G (n). Values around 0.5 have proven to be favorable for the constant ⁇ .
  • the threshold S which is used for the pause decision, is proportional to the estimated value P (n).
  • the relationship S 1.1 P (n) is typical of the relationship between the threshold S and the estimated value P (n).

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  • Engineering & Computer Science (AREA)
  • Computational Linguistics (AREA)
  • Signal Processing (AREA)
  • Health & Medical Sciences (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Human Computer Interaction (AREA)
  • Physics & Mathematics (AREA)
  • Acoustics & Sound (AREA)
  • Multimedia (AREA)
  • Noise Elimination (AREA)
  • Analogue/Digital Conversion (AREA)
  • Telephone Function (AREA)

Claims (8)

1. Dispositif pour la détection des silences dans un signal de parole sur lequel peuvent être superposés des signaux parasites, dans lequel, à chaque moment d'impulsion T(n) d'une cadence, un formateur de valeur moyenne (M) détermine une valeur moyenne à court terme G(n) qui représente une moyenne des grandeurs ou des grandeurs au carré de toutes les valeurs d'échantillonnage du signal de parole perturbé qui sont situées entre les moments d'impulsions T(n-1) et T(n), grâce à quoi peut être déterminée une estimation P(n) de la puissance de bruit qui est fonction de la valeur moyenne à court terme G(n), caractérisé en ce qu'un bloc (PA) détermine une estimation P(n) de la puissance de bruit qui est fonction de la valeur moyenne à court terme G(n) et de l'estimation P(n-1) au moment d'impulsion précédent, qu'une unité (GL) fournit une valeur moyenne à court terme lissée GG(n) qui est obtenue à partir de la valeur moyenne à court terme G(n) du moment et de valeurs moyennes à court terme précédentes, qu'à chaque moment d'impulsion T(n), un comparateur (V) vérifie si la valeur moyenne à court terme lissée GG(n) tombe en dessous d'un premier seuil (S) dépendant de l'estimation P(n) et que, lorsque cette condition a été remplie une fois ou plusieurs fois successivement sans discontinuité, un signal de présence d'un silence est fourni.
2. Dispositif suivant la revendication 1, caractérisé en ce qu'à titre de valeur moyenne à court terme G(n), la moyenne arithmétique des grandeurs des valeurs d'échantillonnage est utilisée.
3. Dispositif suivant la revendication 1, caractérisé en ce que l'estimation P(n) n'est déterminée d'après l'équation
Figure imgb0016
avec une première constante a, que si la différence des valeurs moyennes à court terme G(n) - G(n-1) se situe en valeur absolue en dessous d'un deuxième seuil (D) et que ce cas s'est présenté sans discontinuité pour un nombre (K) de moments d'impulsions précédents, et qu'au cas contraire, l'estimation P(n) est prise égale à l'estimation précédente P(n-1).
4. Dispositif suivant la revendication 1, caractérisé en ce que l'estimation P(n) n'est déterminée d'après l'équation
Figure imgb0017
avec une deuxième constante c, que si l'inégalité
Figure imgb0018
est satisfaite, et qu'au cas contraire, l'estimation P(n) est choisie sous la forme
Figure imgb0019
avec une troisième constante β.
5. Dispositif suivant la revendication 1, caractérisé en ce que le premier seuil (S) est choisi proportionnel à l'estimation P(n).
6. Dispositif suivant la revendication 1, caractérisé en ce que l'unité (GL) prévue pour le lissage lisse trois valeurs moyennes à court terme G(n), G(n-1) et G(n-2) selon la formule
Figure imgb0020
où les constantes co, c" c2 sont toutes supérieures ou égales à zéro et leur somme vaut un.
7. Dispositif suivant la revendication 1, caractérisé en ce que l'unité (GL) prévue pour le lissage a la forme d'un filtre à médiane.
8. Dispositif suivant la revendication 3, caractérisé en ce que le second seuil (D) est choisi proportionnel à la valeur moyenne à court terme G(n).
EP83201638A 1982-11-23 1983-11-17 Dispositif pour la détection des silences dans les signaux de paroles Expired - Lifetime EP0110467B2 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE3243231 1982-11-23
DE19823243231 DE3243231A1 (de) 1982-11-23 1982-11-23 Verfahren zur erkennung von sprachpausen

Publications (3)

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EP0110467A1 EP0110467A1 (fr) 1984-06-13
EP0110467B1 true EP0110467B1 (fr) 1987-08-12
EP0110467B2 EP0110467B2 (fr) 1991-06-19

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US (1) US4700394A (fr)
EP (1) EP0110467B2 (fr)
JP (1) JPS59105695A (fr)
AU (1) AU561076B2 (fr)
CA (1) CA1203627A (fr)
DE (2) DE3243231A1 (fr)

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EP0167364A1 (fr) * 1984-07-06 1986-01-08 AT&T Corp. Détection parole-silence avec codage par sous-bandes
AU583871B2 (en) * 1984-12-31 1989-05-11 Itt Industries, Inc. Apparatus and method for automatic speech recognition
JPH0748695B2 (ja) * 1986-05-23 1995-05-24 株式会社日立製作所 音声符号化方式
DE3626862A1 (de) * 1986-08-08 1988-02-11 Philips Patentverwaltung Mehrstufige sender- antennenkoppeleinrichtung
DE3739681A1 (de) * 1987-11-24 1989-06-08 Philips Patentverwaltung Verfahren zum bestimmen von anfangs- und endpunkt isoliert gesprochener woerter in einem sprachsignal und anordnung zur durchfuehrung des verfahrens
FR2631147B1 (fr) * 1988-05-04 1991-02-08 Thomson Csf Procede et dispositif de detection de signaux vocaux
JP2573352B2 (ja) * 1989-04-10 1997-01-22 富士通株式会社 音声検出装置
US5305422A (en) * 1992-02-28 1994-04-19 Panasonic Technologies, Inc. Method for determining boundaries of isolated words within a speech signal
DE4220524A1 (de) * 1992-06-23 1992-10-22 Matzner Rolf Dipl Ing Verfahren und vorrichtung zur getrennten schaetzung der einzelleistungen zweier stochastischer prozesse aus der beobachtung des durch additive ueberlagerung entstandenen summenprozesses
US5459814A (en) * 1993-03-26 1995-10-17 Hughes Aircraft Company Voice activity detector for speech signals in variable background noise
DE4405723A1 (de) * 1994-02-23 1995-08-24 Daimler Benz Ag Verfahren zur Geräuschreduktion eines gestörten Sprachsignals
DE19730518C1 (de) * 1997-07-16 1999-02-11 Siemens Ag Verfahren und Einrichtung zum Erkennen einer Sprechpause
GB0103242D0 (en) * 2001-02-09 2001-03-28 Radioscape Ltd Method of analysing a compressed signal for the presence or absence of information content
DE10120231A1 (de) * 2001-04-19 2002-10-24 Deutsche Telekom Ag Verfahren und Anordnung zur einkanaligen Geräuschreduktion für gestörte Sprachsignale
CN1867965B (zh) * 2003-10-16 2010-05-26 Nxp股份有限公司 使用自适应噪声基底跟踪的语音活动检测
US8543061B2 (en) 2011-05-03 2013-09-24 Suhami Associates Ltd Cellphone managed hearing eyeglasses
CN104658546B (zh) * 2013-11-19 2019-02-01 腾讯科技（深圳）有限公司 录音处理方法和装置
RU2691603C1 (ru) * 2018-08-22 2019-06-14 Акционерное общество "Концерн "Созвездие" Способ разделения речи и пауз путем анализа значений корреляционной функции помехи и смеси сигнала и помехи

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Also Published As

Publication number Publication date
EP0110467A1 (fr) 1984-06-13
DE3243231A1 (de) 1984-05-24
JPS59105695A (ja) 1984-06-19
DE3373037D1 (en) 1987-09-17
US4700394A (en) 1987-10-13
CA1203627A (fr) 1986-04-22
AU561076B2 (en) 1987-04-30
DE3243231C2 (fr) 1987-07-02
AU2154583A (en) 1984-05-31
EP0110467B2 (fr) 1991-06-19

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