MX2021012603A - Metodo y aparato para determinar un filtro profundo. - Google Patents

Metodo y aparato para determinar un filtro profundo.

Info

Publication number
MX2021012603A
MX2021012603A MX2021012603A MX2021012603A MX2021012603A MX 2021012603 A MX2021012603 A MX 2021012603A MX 2021012603 A MX2021012603 A MX 2021012603A MX 2021012603 A MX2021012603 A MX 2021012603A MX 2021012603 A MX2021012603 A MX 2021012603A
Authority
MX
Mexico
Prior art keywords
deep filter
determining
deep
elements
filter
Prior art date
Application number
MX2021012603A
Other languages
English (en)
Inventor
Emanuel Habets
Wolfgang Mack
Original Assignee
Fraunhofer Ges Forschung
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Fraunhofer Ges Forschung filed Critical Fraunhofer Ges Forschung
Publication of MX2021012603A publication Critical patent/MX2021012603A/es

Links

Classifications

    • 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
    • G10L21/0224—Processing in the time domain
    • 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
    • G10L21/0272—Voice signal separating
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/048—Activation functions
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • 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
    • G10L21/0232—Processing in the frequency domain
    • 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
    • G10L25/27—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the analysis technique
    • G10L25/30—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the analysis technique using neural networks

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Computational Linguistics (AREA)
  • Health & Medical Sciences (AREA)
  • Acoustics & Sound (AREA)
  • Signal Processing (AREA)
  • Multimedia (AREA)
  • Human Computer Interaction (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Quality & Reliability (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • Theoretical Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Mathematical Physics (AREA)
  • Data Mining & Analysis (AREA)
  • Biophysics (AREA)
  • Biomedical Technology (AREA)
  • Computing Systems (AREA)
  • Molecular Biology (AREA)
  • General Health & Medical Sciences (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Software Systems (AREA)
  • Filters That Use Time-Delay Elements (AREA)
  • Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
  • Image Analysis (AREA)
  • Measuring And Recording Apparatus For Diagnosis (AREA)
  • Noise Elimination (AREA)
  • Paper (AREA)
  • Measurement Of Radiation (AREA)

Abstract

Un método para determinar un filtro profundo comprende los siguientes pasos: • recibir una mezcla; • estimar utilizando una red neural profunda el filtro profundo, en donde la estimación se lleva a cabo, tal que el filtro profundo, cuando se aplica a los elementos de la mezcla, obtiene estimaciones de elementos respectivos de las representaciones deseada; en donde el filtro profundo de al menos una dimensión comprende un tensor con elementos.
MX2021012603A 2019-04-16 2020-04-15 Metodo y aparato para determinar un filtro profundo. MX2021012603A (es)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
EP19169585.7A EP3726529A1 (en) 2019-04-16 2019-04-16 Method and apparatus for determining a deep filter
PCT/EP2020/060586 WO2020212419A1 (en) 2019-04-16 2020-04-15 Method and apparatus for determining a deep filter

Publications (1)

Publication Number Publication Date
MX2021012603A true MX2021012603A (es) 2021-11-12

Family

ID=66217806

Family Applications (1)

Application Number Title Priority Date Filing Date
MX2021012603A MX2021012603A (es) 2019-04-16 2020-04-15 Metodo y aparato para determinar un filtro profundo.

Country Status (9)

Country Link
US (1) US20220059114A1 (es)
EP (2) EP3726529A1 (es)
JP (2) JP7486266B2 (es)
KR (1) KR20210153677A (es)
CN (1) CN114041185A (es)
BR (1) BR112021020361A2 (es)
CA (1) CA3136870A1 (es)
MX (1) MX2021012603A (es)
WO (1) WO2020212419A1 (es)

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20210137146A (ko) * 2019-03-10 2021-11-17 카르돔 테크놀로지 엘티디. 큐의 클러스터링을 사용한 음성 증강
WO2021226503A1 (en) 2020-05-08 2021-11-11 Nuance Communications, Inc. System and method for data augmentation for multi-microphone signal processing
GB2620747B (en) * 2022-07-19 2024-10-02 Samsung Electronics Co Ltd Method and apparatus for speech enhancement
US20240112690A1 (en) * 2022-09-26 2024-04-04 Cerence Operating Company Switchable Noise Reduction Profiles

Family Cites Families (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE19948308C2 (de) * 1999-10-06 2002-05-08 Cortologic Ag Verfahren und Vorrichtung zur Geräuschunterdrückung bei der Sprachübertragung
EP2151822B8 (en) * 2008-08-05 2018-10-24 Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. Apparatus and method for processing an audio signal for speech enhancement using a feature extraction
US9881631B2 (en) * 2014-10-21 2018-01-30 Mitsubishi Electric Research Laboratories, Inc. Method for enhancing audio signal using phase information
US9666183B2 (en) * 2015-03-27 2017-05-30 Qualcomm Incorporated Deep neural net based filter prediction for audio event classification and extraction
US10339921B2 (en) * 2015-09-24 2019-07-02 Google Llc Multichannel raw-waveform neural networks
KR102151682B1 (ko) * 2016-03-23 2020-09-04 구글 엘엘씨 다중채널 음성 인식을 위한 적응성 오디오 강화
US11373672B2 (en) * 2016-06-14 2022-06-28 The Trustees Of Columbia University In The City Of New York Systems and methods for speech separation and neural decoding of attentional selection in multi-speaker environments
US10224058B2 (en) * 2016-09-07 2019-03-05 Google Llc Enhanced multi-channel acoustic models
WO2019008580A1 (en) * 2017-07-03 2019-01-10 Yissum Research Development Company Of The Hebrew University Of Jerusalem Ltd. METHOD AND SYSTEM FOR IMPROVING A VOICE SIGNAL OF A HUMAN SPEAKER IN A VIDEO USING VISUAL INFORMATION
CN108417207B (zh) * 2018-01-19 2020-06-30 苏州思必驰信息科技有限公司 一种深度混合生成网络自适应方法及系统
CN109194595B (zh) * 2018-09-26 2020-12-01 东南大学 一种基于神经网络的信道环境自适应ofdm接收方法

Also Published As

Publication number Publication date
EP3726529A1 (en) 2020-10-21
WO2020212419A1 (en) 2020-10-22
US20220059114A1 (en) 2022-02-24
BR112021020361A2 (pt) 2021-12-07
CA3136870A1 (en) 2020-10-22
KR20210153677A (ko) 2021-12-17
CN114041185A (zh) 2022-02-11
JP7486266B2 (ja) 2024-05-17
EP3956888A1 (en) 2022-02-23
JP2022529912A (ja) 2022-06-27
JP2024038369A (ja) 2024-03-19

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