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Missing feature theory with soft spectral subtraction for speaker verification

September 17, 2006
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Conference Paper
Author:
Michael T. Padilla
…
Published in:
Interspeech 2006, ICSLP, 17-21 September 2006.
Topic:
speech enhancement
R&D area:
R&D group:

Summary

This paper considers the problem of training/testing mismatch in the context of speaker verification and, in particular, explores the application of missing feature theory in the case of additive white Gaussian noise corruption in testing. Missing feature theory allows for corrupted features to be removed from scoring, the initial step of which is the detection of these features. One method of detection, employing spectral subtraction, is studied in a controlled manner and it is shown that with missing feature compensation the resulting verification performance is improved as long as a minimum number of features remain. Finally, a blending of "soft" spectral subtraction for noise mitigation and missing feature compensation is presented. The resulting performance improves on the constituent techniques alone, reducing the equal error rate by about 15% over an SNR range of 5 - 25 dB.
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Summary

This paper considers the problem of training/testing mismatch in the context of speaker verification and, in particular, explores the application of missing feature theory in the case of additive white Gaussian noise corruption in testing. Missing feature theory allows for corrupted features to be removed from scoring, the initial step...

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Missing feature theory with soft spectral subtraction for speaker verification

An overview of automatic speaker diarization systems

September 1, 2006
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Journal Article
Author:
Sue E. Tranter
…
Published in:
IEEE Trans. Audio, Speech, and Language Processing, Vol. 14, No. 5, September 2006, pp. 1557-1565.
Topic:
speaker recognition
R&D area:
R&D group:

Summary

Audio diarization is the process of annotating an input audio channel with information that attributes (possibly overlapping) temporal regions of signal energy to their specific sources. These sources can include particular speakers, music, background noise sources, and other signal source/channel characteristics. Diarization can be used for helping speech recognition, facilitating the searching and indexing of audio archives, and increasing the richness of automatic transcriptions, making them more readable. In this paper, we provide an overview of the approaches currently used in a key area of audio diarization, namely speaker diarization, and discuss their relative merits and limitations. Performances using the different techniques are compared within the framework of the speaker diarization task in the DARPA EARS Rich Transcription evaluations. We also look at how the techniques are being introduced into real broadcast news systems and their portability to other domains and tasks such as meetings and speaker verification.
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Summary

Audio diarization is the process of annotating an input audio channel with information that attributes (possibly overlapping) temporal regions of signal energy to their specific sources. These sources can include particular speakers, music, background noise sources, and other signal source/channel characteristics. Diarization can be used for helping speech recognition, facilitating...

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An overview of automatic speaker diarization systems

Synthesis, analysis, and pitch modification of the breathy vowel

October 16, 2005
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Conference Paper
Author:
Daryush Mehta
…
Published in:
2005 Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), 16-19 October 2005, pp. 199-202.
Topic:
speech enhancement
R&D area:
R&D group:

Summary

Breathiness is an aspect of voice quality that is difficult to analyze and synthesize, especially since its periodic and noise components are typically overlapping in frequency. The decomposition and manipulation of these two components is of importance in a variety of speech application areas such as text-to-speech synthesis, speech encoding, and clinical assessment of disordered voices. This paper first investigates the perceptual relevance of a speech production model that assumes the speech noise component is modulated by the glottal airflow waveform. After verifying the importance of noise modulation in breathy vowels, we use the modulation model to address the particular problem of pitch modification of this signal class. Using a decomposition method referred to as pitch-scaled harmonic filtering to extract the additive noise component, we introduce a pitch modification algorithm that explicitly modifies the modulation characteristic of this noise component. The approach applies envelope shaping to the noise source that is derived from the inverse-filtered noise component. Modification examples using synthetic and real breathy vowels indicate promising performance with spectrally-overlapping periodic and noise components.
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Summary

Breathiness is an aspect of voice quality that is difficult to analyze and synthesize, especially since its periodic and noise components are typically overlapping in frequency. The decomposition and manipulation of these two components is of importance in a variety of speech application areas such as text-to-speech synthesis, speech encoding...

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Synthesis, analysis, and pitch modification of the breathy vowel

A comparison of soft and hard spectral subtraction for speaker verification

October 4, 2004
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Conference Paper
Author:
Michael T. Padilla
…
Published in:
8th Int. Conf. on Spoken Language Processing, ICSLP 2004, 4-8 October 2004.
Topic:
speech enhancement
R&D area:
R&D group:

Summary

An important concern in speaker recognition is the performance degradation that occurs when speaker models trained with speech from one type of channel are subsequently used to score speech from another type of channel, known as channel mismatch. This paper investigates the relative performance of two different spectral subtraction methods for additive noise compensation in the context of speaker verification. The first method, termed "soft" spectral subtraction, is performed in the spectral domain on the |DFT|^2 values of the speech frames while the second method, termed "hard" spectral subtraction, is performed on the Mel-filter energy features. It is shown through both an analytical argument as well as a simulation that soft spectral subtraction results in a higher signal-to-noise ratio in the resulting Mel-filter energy features. In the context of Gaussian mixture model-based speaker verification with additive noise in testing utterances, this is shown to result in an equal error rate improvement over a system without spectral subtraction of approximately 7% in absolute terms, 21% in relative terms, over an additive white Gaussian noise range of 5-25 dB.
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Summary

An important concern in speaker recognition is the performance degradation that occurs when speaker models trained with speech from one type of channel are subsequently used to score speech from another type of channel, known as channel mismatch. This paper investigates the relative performance of two different spectral subtraction methods...

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A comparison of soft and hard spectral subtraction for speaker verification

Automated lip-reading for improved speech intelligibility

January 1, 2004
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Conference Paper
Author:
Matthew R. McClain
…
Published in:
Proc. of the IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, ICASSP, Vol. I, 17-21 May 2004, pp. I-701 - I-704.
Topic:
speech processing
R&D area:
R&D group:

Summary

Various psycho-acoustical experiments have concluded that visual features strongly affect the perception of speech. This contribution is most pronounced in noisy environments where the intelligibility of audio-only speech is quickly degraded. An exploration of the effectiveness for extracted visual features such as lip height and width for improving speech intelligibility in noisy environments is provided in this paper. The intelligibility content of these extracted visual features will be investigated through an intelligibility test on an animated rendition of the video generated from the extracted visual features, as well as on the original video. These experiments demonstrate that the extracted video features do contain important aspects of intelligibility that may be utilized in augmenting speech enhancement and coding applications. Alternatively, these extracted visual features can be transmitted in a bandwidth effective way to augment speech coders.
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Summary

Various psycho-acoustical experiments have concluded that visual features strongly affect the perception of speech. This contribution is most pronounced in noisy environments where the intelligibility of audio-only speech is quickly degraded. An exploration of the effectiveness for extracted visual features such as lip height and width for improving speech intelligibility...

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Automated lip-reading for improved speech intelligibility

Exploiting nonacoustic sensors for speech enhancement

December 11, 2003
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Conference Paper
Author:
Thomas F. Quatieri
…
Published in:
Proc. Workshop on Multimodal User Authentication, 11-12 December 2003, pp. 66-73.
Topic:
speaker recognition
R&D area:
R&D group:

Summary

Nonacoustic sensors such as the general electromagnetic motion sensor (GEMS), the physiological microphone (P-mic), and the electroglottograph (EGG) offer multimodal approaches to speech processing and speaker and speech recognition. These sensors provide measurements of functions of the glottal excitation and, more generally, of the vocal tract articulator movements that are relatively immune to acoustic disturbances and can supplement the acoustic speech waveform. This paper describes an approach to speech enhancement that exploits these nonacoustic sensors according to their capability in representing specific speech characteristics in different frequency bands. Frequency-domain sensor phase, as well as magnitude, is found to contribute to signal enhancement. Preliminary testing involves the time-synchronous multi-sensor DARPA Advanced Speech Encoding Pilot Speech Corpus collected in a variety of harsh acoustic noise environments. The enhancement approach is illustrated with examples that indicate its applicability as a pre-processor to low-rate vocoding and speaker authentication, and for enhanced listening from degraded speech.
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Summary

Nonacoustic sensors such as the general electromagnetic motion sensor (GEMS), the physiological microphone (P-mic), and the electroglottograph (EGG) offer multimodal approaches to speech processing and speaker and speech recognition. These sensors provide measurements of functions of the glottal excitation and, more generally, of the vocal tract articulator movements that are...

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Exploiting nonacoustic sensors for speech enhancement

Multimodal speaker authentication using nonacuostic sensors

December 11, 2003
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Conference Paper
Author:
William M. Campbell
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Published in:
Proc. Workshop on Multimodal User Authentication, 11-12 December 2003, pp. 215-222.
Topic:
speech enhancement
R&D area:
R&D group:

Summary

Many nonacoustic sensors are now available to augment user authentication. Devices such as the GEMS (glottal electromagnetic micro-power sensor), the EGG (electroglottograph), and the P-mic (physiological mic) all have distinct methods of measuring physical processes associated with speech production. A potential exciting aspect of the application of these sensors is that they are less influenced by acoustic noise than a microphone. A drawback of having many sensors available is the need to develop features and classification technologies appropriate to each sensor. We therefore learn feature extraction based on data. State of the art classification with Gaussian Mixture Models and Support Vector Machines is then applied for multimodal authentication. We apply our techniques to two databases--the Lawrence Livermore GEMS corpus and the DARPA Advanced Speech Encoding Pilot corpus. We show the potential of nonacoustic sensors to increase authentication accuracy in realistic situations.
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Summary

Many nonacoustic sensors are now available to augment user authentication. Devices such as the GEMS (glottal electromagnetic micro-power sensor), the EGG (electroglottograph), and the P-mic (physiological mic) all have distinct methods of measuring physical processes associated with speech production. A potential exciting aspect of the application of these sensors is...

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Multimodal speaker authentication using nonacuostic sensors

2-D processing of speech with application to pitch estimation

September 16, 2002
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Conference Paper
Author:
Thomas F. Quatieri
Published in:
7th Int. Conf. on Spoken Language Processing, ICSLP 2002, 16-20 September 2002.
Topic:
speech enhancement
R&D area:
R&D group:

Summary

In this paper, we introduce a new approach to two-dimensional (2-D) processing of the one-dimensional (1-D) speech signal in the time-frequency plane. Specifically, we obtain the shortspace 2-D Fourier transform magnitude of a narrowband spectrogram of the signal and show that this 2-D transformation maps harmonically-related signal components to a concentrated entity in the new 2-D plane. We refer to this series of operations as the "grating compression transform" (GCT), consistent with sine-wave grating patterns in the spectrogram reduced to smeared impulses. The GCT forms the basis of a speech pitch estimator that uses the radial distance to the largest peak in the GCT plane. Using an average magnitude difference between pitch-contour estimates, the GCT-based pitch estimator is shown to compare favorably to a sine-wave-based pitch estimator for all-voiced speech in additive white noise. An extension to a basis for two-speaker pitch estimation is also proposed.
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Summary

In this paper, we introduce a new approach to two-dimensional (2-D) processing of the one-dimensional (1-D) speech signal in the time-frequency plane. Specifically, we obtain the shortspace 2-D Fourier transform magnitude of a narrowband spectrogram of the signal and show that this 2-D transformation maps harmonically-related signal components to a...

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2-D processing of speech with application to pitch estimation

Speech enhancement based on auditory spectral change

May 13, 2002
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Conference Paper
Author:
Thomas F. Quatieri
…
Published in:
Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, ICASSP, Vol. I, Speech Processing Neural Networks for Signal Processing, 13-17 May 2002, pp. I-257 - I-260.
Topic:
speech enhancement
R&D area:
R&D group:

Summary

In this paper, an adaptive approach to the enhancement of speech signals is developed based on auditory spectral change. The algorithm is motivated by sensitivity of aural biologic systems to signal dynamics, by evidence that noise is aurally masked by rapid changes in a signal, and by analogies to these two aural phenomena in biologic visual processing. Emphasis is on preserving nonstationarity, i.e., speech transient and time-varying components, such as plosive bursts, formant transitions, and vowel onsets, while suppressing additive noise. The essence of the enhancement technique is a Wiener filter that uses a desired signal spectrum whose estimation adapts to stationarity of the measured signal. The degree of stationarity is derived from a signal change measurement, based on an auditory spectrum that accentuates change in spectral bands. The adaptive filter is applied in an unconventional overlap-add analysis/synthesis framework, using a very short 4-ms analysis window and a 1-ms frame interval. In informal listening, the reconstructions are judged to be "crisp" corresponding to good temporal resolution of transient and rapidly-moving speech events.
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Summary

In this paper, an adaptive approach to the enhancement of speech signals is developed based on auditory spectral change. The algorithm is motivated by sensitivity of aural biologic systems to signal dynamics, by evidence that noise is aurally masked by rapid changes in a signal, and by analogies to these...

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Speech enhancement based on auditory spectral change

'Perfect reconstruction' time-scaling filterbanks

March 15, 1999
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Conference Paper
Author:
Thomas F. Quatieri
…
Published in:
Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, ICASSP, Vol. III, 15-19 March 1999, pp. 945-948.
Topic:
speech enhancement
R&D area:
R&D group:

Summary

A filterbank-based method of time-scale modification is analyzed for elemental signals including clicks, sines, and AM-FM sines. It is shown that with the use of some basic properties of linear systems, as well as FM-to-AM filter transduction, "perfect reconstruction" time-scaling filterbanks can be constructed for these elemental signal classes under certain conditions on the filterbank. Conditions for perfect reconstruction time-scaling are shown analytically for the uniform filterbank case, while empirically for the nonuniform constant-Q (gammatone) case. Extension of perfect reconstruction to multi-component signals is shown to require both filterbank and signal-dependent conditions and indicates the need for a more complete theory of "perfect reconstruction" time-scaling filterbanks.
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Summary

A filterbank-based method of time-scale modification is analyzed for elemental signals including clicks, sines, and AM-FM sines. It is shown that with the use of some basic properties of linear systems, as well as FM-to-AM filter transduction, "perfect reconstruction" time-scaling filterbanks can be constructed for these elemental signal classes under...

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'Perfect reconstruction' time-scaling filterbanks
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