EP1850328A1 - Verstärkung und Extraktion von Sprachsignalformanten - Google Patents

Verstärkung und Extraktion von Sprachsignalformanten Download PDF

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Publication number
EP1850328A1
EP1850328A1 EP06013126A EP06013126A EP1850328A1 EP 1850328 A1 EP1850328 A1 EP 1850328A1 EP 06013126 A EP06013126 A EP 06013126A EP 06013126 A EP06013126 A EP 06013126A EP 1850328 A1 EP1850328 A1 EP 1850328A1
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EP
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Prior art keywords
formants
filters
filtering
audio signal
frequency conversion
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Withdrawn
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EP06013126A
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English (en)
French (fr)
Inventor
Frank Joublin Dr.
Martin Heckmann Dr.
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Honda Research Institute Europe GmbH
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Honda Research Institute Europe GmbH
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Priority to EP06013126A priority Critical patent/EP1850328A1/de
Priority to JP2007061984A priority patent/JP2007293285A/ja
Publication of EP1850328A1 publication Critical patent/EP1850328A1/de
Withdrawn legal-status Critical Current

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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
    • 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
    • G10L21/0316—Speech enhancement, e.g. noise reduction or echo cancellation by changing the amplitude
    • G10L21/0364—Speech enhancement, e.g. noise reduction or echo cancellation by changing the amplitude for improving intelligibility
    • 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
    • G10L25/03—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters
    • G10L25/15—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters the extracted parameters being formant information

Definitions

  • the present invention generally relates to the processing of voice signals in order to enhance characteristics which are useful for a further technical use of the processed voice signal.
  • the invention particularly relates to the enhancement and extraction of formants from audio signals such as e.g. speech signals.
  • the proposed processing is useful e.g. for hearing aids, automatic speech recognition and the training of artificial speech synthesis with the extracted formants.
  • Formants are the distinguishing or meaningful frequency components of human speech. According to one definition (see e.g. http://en.wikipedia.org/wiki/Formants also for more details and citations) a formant is a peak in an acoustic frequency spectrum which results from the resonant frequencies of any acoustical system (acoustical tube). It is most commonly invoked in phonetics or acoustics involving the resonant frequencies of vocal tracts.
  • the detection of formants is useful e.g. in the framework of speech recognition systems and speech synthesizing systems.
  • Today's speech recognition systems work very good in well controlled, low-noise environments but show severe performance degradation when the distances between the speaker and the microphone varies or noise is present.
  • the formant frequencies i. e. the resonance frequencies of the vocal tract, are one of the cues for speech recognition.
  • Vowels are mostly recognized based on the formant frequencies and their transitions and also for consonants they play a very important role.
  • a different applicability of the formant transitions is their use for speech synthesis.
  • synthesis systems based on the concatenation of prerecorded blocks perform significantly better than those using directly formants or vocal tract filter shapes. But this is rather due to the difficulty in finding the right parameterization of these models and not an intrinsic problem to the sound generation.
  • driving such a formant based synthesis system with parameters extracted from measurements on humans produces naturally sounding speech.
  • Formant extraction algorithms can be used to perform this determination of the articulation parameters from large corpuses of speech and a learning algorithm can be developed which determines their correct setting during the speech synthesis process.
  • bandpass filters and first order LPC analysis to extract the formants.
  • the bandpass center frequencies are adapted based on the found location in the previous time step. Additionally a voiced/unvoiced decision is incorporated in the formant extraction.
  • a first aspect of the invention relates to a method for enhancing the formants of an audio signal, the method comprising the following steps:
  • the size of the filters used in step b.) can be adapted, in a configuration step, depending on center frequencies of the frequency conversion step.
  • the size of the filters used in step b.) can be adapted corresponding to the spectral resolution of the frequency conversion step.
  • the size of the filters used in step b.) can be adapted corresponding to expected formants which e.g. occur typically in speech signals.
  • step b. the fundamental frequency of the audio signal can be estimated and then essentially eliminated.
  • step b. the spectral distribution of the excitation of the acoustic tube can be estimated and an amplification of the spectrogram with the inverse of this distribution can be performed.
  • the envelope of the signal can be determined e.g. via rectification and low-pass filtering.
  • a Gammatone filter bank can be used for the frequency conversion step.
  • a reconstructive filtering can be applied on the result of step b.).
  • the reconstructive filtering can use filters adapted to the expected formants of the supplied audio signal, and the reconstruction is done by adding the impulse response of the used filters weighted with the response when filtering with said filter.
  • Pair Gabor filters can be used for the reconstructive filtering.
  • the width of the reconstructing filters is adapted corresponding to the spectral resolution of the frequency conversion step or the mean bandwidths of preset formants expected to be present in the supplied audio signal.
  • the enhanced formants can then be extracted from the signal for further use.
  • the method of enhancing the formants can be used e.g. for speech enhancement.
  • the method can be used together with a tracking algorithm in order to carry out a speech recognition on the supplied audio signal.
  • the method can be used to train artificial speech synthesis systems with the extracted formants.
  • the invention also relates to a computer program product, implementing such a method.
  • the invention further relates to a hearing aid comprising a computing unit designed to implement such a method.
  • the invention proposes a method and a system (see figure 10) which enhances the formants in the spectrogram and allows a subsequent extraction of the enhanced formants.
  • the invention proposes to apply e.g. a Gammatone filter bank on a supplied audio signal representation to obtain a spectro-temporal representation of the signals.
  • the audio signal is converted in the frequency domain.
  • the first stage in the system as shown in figure 10 is the application of a Gammatone filter bank on the signal.
  • the filter bank has e.g. 128 channels ranging from e.g. 80Hz to 5 kHz. From this signal the envelope is calculated via rectification and low-pass filtering. In Fig. 1 the results of this processing can be seen.
  • the fundamental frequency of voiced signal parts can be estimated and subsequently eliminated from the spectrogram.
  • the energy of the fundamental frequency is normally much higher than that of the harmonics.
  • the invention proposes to eliminate the fundamental frequency of voiced signal parts from the spectrogram.
  • an algorithm based on a histogram of zero crossing distances can be used to estimate the fundamental frequency.
  • any pitch estimation algorithm can be used for the estimation of the fundamental frequency.
  • the filter channels in the neighborhood of the found fundamental frequency are set to the noise floor.
  • a smoothing in the time domain and an optional sub-sampling is performed.
  • a filtering along the channel axis is performed.
  • the size of the filtering kernel is changed position-dependent, i. e. with wide kernels at low frequencies and narrow kernels at high frequencies. This takes into account the logarithmic arrangement of the center frequencies in the Gammatone filter bank.
  • the energy of the glottal excitation signal shows a general decay with frequency. Therefore low formants being excited by low harmonics have much more energy than high formants. In a similar way the noise like excitation, which has mostly energy in the high frequencies, has a much lower overall energy than the harmonic excitation. As a consequence in a speech signal the energy in the low frequencies is much higher than in the high frequencies.
  • a pre-emphasis of the spectrogram This pre-emphasis raises the energy of the high frequencies (compare Fig. 3).
  • a known way is to use a high-pass filter but as the audio signal is already represented in the spectro-temporal domain the invention proposes to weight the energy of the filter channels with an exponentially decreasing weight from the high to the low frequencies. Subsequently a smoothing along the frequency axis is carried out. Via this smoothing the energy of the single harmonics is spread and peaks at the formant location form.
  • the size of the smoothing kernel has to be set depending on the center frequencies. It has to be wide at low frequencies where the filter bandwidths and hence the increment of the center frequencies is low in order to cover the necessary frequency range.
  • Figure 4 shows the results of this operation.
  • the resulting spectrogram contains negative values due to the application of the Mexican Hat. Depending on the further processing it can be beneficial to set these negative values to zero, but in our case they have been kept as they permit a better enhancement of the formant tracks.
  • the formants were extracted from a synthetically generated speech signal for which we know the correct formant positions.
  • the system used for speech synthesis is ipox (see A. Dikensen and J. Coleman, "All-prosodic speech synthesis"in Progress in Speech Synthesis, J. P. H. van Santen, R. W. Sproat, J. P. Olive, and J. Hirschberg, Eds., pp.91-108. Springer, New York, 1995 .)
  • the ipox system is a compilation of rules which allows to generate words from phonemic input. More precisely it produces parameter files for the Klatt80 formant synthesizer. As test sentence"Five women played basketball” generated by a male voice has been used. By mixing babble noise from the Noisex database with varying SNR to the signal we can evaluate the robustness of the formant extraction process to additional noise.
  • Fig. 7 the result of the same signal with babble noise added at an SNR of 20 dB is shown. The location of the peaks is hardly affected by the additional noise.
  • Figure 11 shows a block diagram of the reconstructive filtering.
  • the result of the previous enhancement is filtered with a set of n parallel filters whose impulse responses are adapted to the expected structure.
  • This can for example be a set of n even Gabor filters with different orientations and frequencies.
  • Gabor filters are known to the skilled person and can be defined as linear filters whose impulse response is defined by a harmonic function multiplied by a Gaussian function.
  • the impulse responses (receptive fields) of these filters are then respectively weighted with the corresponding response when applying the filter to the data, i.e. the result of the preceding filtering step. Therefore during the reconstruction the filter does not only generate one single point at the center of the filter but a structure corresponding to the whole area of the impulse response.
  • the invention can be applied to the enhancement of speech signals, especially for the hearing impaired as it is known that enhancing the formants increases intelligibility for them.

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  • Engineering & Computer Science (AREA)
  • Computational Linguistics (AREA)
  • Quality & Reliability (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)
  • Compression, Expansion, Code Conversion, And Decoders (AREA)
EP06013126A 2006-04-26 2006-06-26 Verstärkung und Extraktion von Sprachsignalformanten Withdrawn EP1850328A1 (de)

Priority Applications (2)

Application Number Priority Date Filing Date Title
EP06013126A EP1850328A1 (de) 2006-04-26 2006-06-26 Verstärkung und Extraktion von Sprachsignalformanten
JP2007061984A JP2007293285A (ja) 2006-04-26 2007-03-12 音声信号のフォルマントの強調および抽出

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
EP06008675 2006-04-26
EP06013126A EP1850328A1 (de) 2006-04-26 2006-06-26 Verstärkung und Extraktion von Sprachsignalformanten

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EP1850328A1 true EP1850328A1 (de) 2007-10-31

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Cited By (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2232700A1 (de) * 2007-12-21 2010-09-29 Srs Labs, Inc. System zur einstellung der wahrgenommenen lautstärke von tonsignalen
US8538042B2 (en) 2009-08-11 2013-09-17 Dts Llc System for increasing perceived loudness of speakers
WO2014039028A1 (en) * 2012-09-04 2014-03-13 Nuance Communications, Inc. Formant dependent speech signal enhancement
WO2015147363A1 (ko) * 2014-03-28 2015-10-01 숭실대학교산학협력단 차신호 주파수 프레임 비교법에 의한 음주 판별 방법, 이를 수행하기 위한 기록 매체 및 장치
WO2015147362A1 (ko) * 2014-03-28 2015-10-01 숭실대학교산학협력단 차신호 고주파 신호의 비교법에 의한 음주 판별 방법, 이를 수행하기 위한 기록 매체 및 장치
US9312829B2 (en) 2012-04-12 2016-04-12 Dts Llc System for adjusting loudness of audio signals in real time
CN106486110A (zh) * 2016-10-21 2017-03-08 清华大学 一种支持语音实时分解/合成的伽马通滤波器组芯片***
US9613633B2 (en) 2012-10-30 2017-04-04 Nuance Communications, Inc. Speech enhancement
EP3113183A4 (de) * 2014-02-28 2017-07-26 National Institute of Information and Communications Technology Sprachklärungsvorrichtung und computerprogramm dafür
US9899039B2 (en) 2014-01-24 2018-02-20 Foundation Of Soongsil University-Industry Cooperation Method for determining alcohol consumption, and recording medium and terminal for carrying out same
US9916844B2 (en) 2014-01-28 2018-03-13 Foundation Of Soongsil University-Industry Cooperation Method for determining alcohol consumption, and recording medium and terminal for carrying out same
US9934793B2 (en) 2014-01-24 2018-04-03 Foundation Of Soongsil University-Industry Cooperation Method for determining alcohol consumption, and recording medium and terminal for carrying out same
US9943260B2 (en) 2014-03-28 2018-04-17 Foundation of Soongsil University—Industry Cooperation Method for judgment of drinking using differential energy in time domain, recording medium and device for performing the method

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP5313528B2 (ja) * 2008-03-18 2013-10-09 リオン株式会社 補聴器の信号処理方法

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US4820059A (en) * 1985-10-30 1989-04-11 Central Institute For The Deaf Speech processing apparatus and methods
EP0742548A2 (de) * 1995-05-12 1996-11-13 Mitsubishi Denki Kabushiki Kaisha Vorrichtung und Verfahren zur Sprachkodierung unter Verwendung eines Filters zur Verbesserung der Signalqualität
US6223151B1 (en) * 1999-02-10 2001-04-24 Telefon Aktie Bolaget Lm Ericsson Method and apparatus for pre-processing speech signals prior to coding by transform-based speech coders
US20050165608A1 (en) * 2002-10-31 2005-07-28 Masanao Suzuki Voice enhancement device
US20050197832A1 (en) * 2003-12-31 2005-09-08 Hearworks Pty Limited Modulation depth enhancement for tone perception
EP1600947A2 (de) * 2004-05-26 2005-11-30 Honda Research Institute Europe GmbH Subtraktive Reduktion von harmonischen Störgeräuschen

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US4820059A (en) * 1985-10-30 1989-04-11 Central Institute For The Deaf Speech processing apparatus and methods
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Cited By (28)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2232700A4 (de) * 2007-12-21 2012-10-10 Dts Llc System zur einstellung der wahrgenommenen lautstärke von tonsignalen
US8315398B2 (en) 2007-12-21 2012-11-20 Dts Llc System for adjusting perceived loudness of audio signals
EP2232700A1 (de) * 2007-12-21 2010-09-29 Srs Labs, Inc. System zur einstellung der wahrgenommenen lautstärke von tonsignalen
US9264836B2 (en) 2007-12-21 2016-02-16 Dts Llc System for adjusting perceived loudness of audio signals
US8538042B2 (en) 2009-08-11 2013-09-17 Dts Llc System for increasing perceived loudness of speakers
US9820044B2 (en) 2009-08-11 2017-11-14 Dts Llc System for increasing perceived loudness of speakers
US10299040B2 (en) 2009-08-11 2019-05-21 Dts, Inc. System for increasing perceived loudness of speakers
US9312829B2 (en) 2012-04-12 2016-04-12 Dts Llc System for adjusting loudness of audio signals in real time
US9559656B2 (en) 2012-04-12 2017-01-31 Dts Llc System for adjusting loudness of audio signals in real time
WO2014039028A1 (en) * 2012-09-04 2014-03-13 Nuance Communications, Inc. Formant dependent speech signal enhancement
CN104704560B (zh) * 2012-09-04 2018-06-05 纽昂斯通讯公司 共振峰依赖的语音信号增强
DE112012006876B4 (de) * 2012-09-04 2021-06-10 Cerence Operating Company Verfahren und Sprachsignal-Verarbeitungssystem zur formantabhängigen Sprachsignalverstärkung
CN104704560A (zh) * 2012-09-04 2015-06-10 纽昂斯通讯公司 共振峰依赖的语音信号增强
US9805738B2 (en) 2012-09-04 2017-10-31 Nuance Communications, Inc. Formant dependent speech signal enhancement
US9613633B2 (en) 2012-10-30 2017-04-04 Nuance Communications, Inc. Speech enhancement
US9934793B2 (en) 2014-01-24 2018-04-03 Foundation Of Soongsil University-Industry Cooperation Method for determining alcohol consumption, and recording medium and terminal for carrying out same
US9899039B2 (en) 2014-01-24 2018-02-20 Foundation Of Soongsil University-Industry Cooperation Method for determining alcohol consumption, and recording medium and terminal for carrying out same
US9916844B2 (en) 2014-01-28 2018-03-13 Foundation Of Soongsil University-Industry Cooperation Method for determining alcohol consumption, and recording medium and terminal for carrying out same
EP3113183A4 (de) * 2014-02-28 2017-07-26 National Institute of Information and Communications Technology Sprachklärungsvorrichtung und computerprogramm dafür
US9842607B2 (en) 2014-02-28 2017-12-12 National Institute Of Information And Communications Technology Speech intelligibility improving apparatus and computer program therefor
US9907509B2 (en) 2014-03-28 2018-03-06 Foundation of Soongsil University—Industry Cooperation Method for judgment of drinking using differential frequency energy, recording medium and device for performing the method
US9916845B2 (en) 2014-03-28 2018-03-13 Foundation of Soongsil University—Industry Cooperation Method for determining alcohol use by comparison of high-frequency signals in difference signal, and recording medium and device for implementing same
US9943260B2 (en) 2014-03-28 2018-04-17 Foundation of Soongsil University—Industry Cooperation Method for judgment of drinking using differential energy in time domain, recording medium and device for performing the method
CN106133833A (zh) * 2014-03-28 2016-11-16 崇实大学校产学协力团 通过差分信号中的高频信号的比较确定饮酒的方法以及用于实现该方法的记录介质和装置
WO2015147362A1 (ko) * 2014-03-28 2015-10-01 숭실대학교산학협력단 차신호 고주파 신호의 비교법에 의한 음주 판별 방법, 이를 수행하기 위한 기록 매체 및 장치
WO2015147363A1 (ko) * 2014-03-28 2015-10-01 숭실대학교산학협력단 차신호 주파수 프레임 비교법에 의한 음주 판별 방법, 이를 수행하기 위한 기록 매체 및 장치
CN106486110A (zh) * 2016-10-21 2017-03-08 清华大学 一种支持语音实时分解/合成的伽马通滤波器组芯片***
CN106486110B (zh) * 2016-10-21 2019-11-08 清华大学 一种支持语音实时分解/合成的伽马通滤波器组芯片***

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