NDLI: Postfilters to modify the modulation spectrum for statistical parametric speech synthesis

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IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP) : Volume 24

Issue 9, September 2016

Joint argument inference in chinese event extraction with argument consistency and event relevance

Proportionate adaptive filtering for block-sparse system identification

Noise reduction with optimal variable span linear filters

Enhancement and noise statistics estimation for non-stationary voiced speech

Relationships between vocal function measures derived from an acoustic microphone and a subglottal neck-surface accelerometer

Unsupervised word segmentation and lexicon discovery using acoustic word embeddings

Joint dereverberation and noise reduction based on acoustic multi-channel equalization

Deep sentence embedding using long short-term memory networks: analysis and application to information retrieval

Theory and perceptual evaluation of the binaural reproduction and beamforming tradeoff in the generalized spherical array beamformer

A single-channel non-intrusive C50 estimator correlated with speech recognition performance

Exploiting turn-taking temporal evolution for personality trait perception in dyadic conversations

Empirical use of information retrieval to build synthetic data for SMT domain adaptation

Postfilters to modify the modulation spectrum for statistical parametric speech synthesis

Anti-spoofing for text-independent speaker verification: an initial database, comparison of countermeasures, and human performance

Adaptive time-frequency analysis for noise reduction in an audio filter bank with low delay

A joint training framework for robust automatic speech recognition

Learning representations for nonspeech audio events through their similarities to speech patterns

Issue 3, March 2016

Issue 2, February 2016

Issue 1, January 2016

IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP) : Volume 23

IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP) : Volume 22

Postfilters to modify the modulation spectrum for statistical parametric speech synthesis

Content Provider	ACM Digital Library
Author	Nakamura, Satoshi Toda, Tomoki Takamichi, Shinnosuke Neubig, Graham Black, Alan W. Sakti, Sakriani
Copyright Year	2016
Abstract	This paper presents novel approaches based on modulation spectrum (MS) for high-quality statistical parametric speech synthesis, including text-to-speech (TTS) and voice conversion (VC). Although statistical parametric speech synthesis offers various advantages over concatenative speech synthesis, the synthetic speech quality is still not as good as that of con-catenative speech synthesis or the quality of natural speech. One of the biggest issues causing the quality degradation is the over-smoothing effect often observed in the generated speech parameter trajectories. Global variance (GV) is known as a feature well correlated with the over-smoothing effect, and the effectiveness of keeping the GV of the generated speech parameter trajectories similar to those of natural speech has been confirmed. However, the quality gap between natural speech and synthetic speech is still large. In this paper, we propose using the MS of the generated speech parameter trajectories as a new feature to effectively quantify the over-smoothing effect. Moreover, we propose post-filters to modify the MS utterance by utterance or segment by segment to make the MS of synthetic speech close to that of natural speech. The proposed postfilters are applicable to various synthesizers based on statistical parametric speech synthesis. We first perform an evaluation of the proposed method in the framework of hidden Markov model (HMM)-based TTS, examining its properties from different perspectives. Furthermore, effectiveness of the proposed postfilters are also evaluated in Gaussian mixture model (GMM)-based VC and classification and regression trees (CART)-based TTS (a.k.a., CLUSTERGEN). The experimental results demonstrate that 1) the proposed utterance-level postfilter achieves quality comparable to the conventional generation algorithm considering the GV, and yields significant improvements by applying to the GV-based generation algorithm in HMM-based TTS, 2) the proposed segment-level postfilter capable of achieving low-delay synthesis also yields significant improvements in synthetic speech quality, and 3) the proposed postfilters are also effective in not only HMM-based TTS but also GMM-based VC and CLUSTERGEN.
Starting Page	755
Ending Page	767
Page Count	13
File Format	PDF
ISSN	23299290
e-ISSN	23299304
Volume Number	24
Issue Number	4
Journal	IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-04-01
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	CLUSTERGEN GMM-based voice conversion HMM-based text-to-speech Global variance Modulation spectrum Over-smoothing Post-filter Statistical parametric speech synthesis
Content Type	Text
Resource Type	Article
Subject	Instrumentation Computational Mathematics Signal Processing Electrical and Electronic Engineering Acoustics and Ultrasonics Speech and Hearing Media Technology

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A postfilter to modify the modulation spectrum in HMM-based speech synthesis

Modulation spectrum-constrained trajectory training algorithm for GMM-based Voice Conversion

Parameter generation algorithm considering Modulation Spectrum for HMM-based speech synthesis

Modulation spectrum-based post-filter for GMM-based Voice Conversion

A Deep Generative Architecture for Postfiltering in Statistical Parametric Speech Synthesis

Post-Filters to Modify the Modulation Spectrum for Statistical Parametric Speech Synthesis

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INTERSPEECH 2006- ICSLP CLUSTERGEN: A Statistical Parametric Synthesizer using Trajectory Modeling

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Postfilters to modify the modulation spectrum for statistical parametric speech synthesis

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