IEEE Transactions on Audio Speech and Language Processing最新文献_第9页

Model-Based Multiple Pitch Tracking Using Factorial HMMs: Model Adaptation and Inference 基于模型的多音高跟踪:模型自适应与推理

IEEE Transactions on Audio Speech and Language Processing Pub Date : 2013-08-01 DOI: 10.1109/TASL.2013.2260744

Michael Wohlmayr, F. Pernkopf

{"title":"Model-Based Multiple Pitch Tracking Using Factorial HMMs: Model Adaptation and Inference","authors":"Michael Wohlmayr, F. Pernkopf","doi":"10.1109/TASL.2013.2260744","DOIUrl":"https://doi.org/10.1109/TASL.2013.2260744","url":null,"abstract":"Robustness against noise and interfering audio signals is one of the challenges in speech recognition and audio analysis technology. One avenue to approach this challenge is single-channel multiple-source modeling. Factorial hidden Markov models (FHMMs) are capable of modeling acoustic scenes with multiple sources interacting over time. While these models reach good performance on specific tasks, there are still serious limitations restricting the applicability in many domains. In this paper, we generalize these models and enhance their applicability. In particular, we develop an EM-like iterative adaptation framework which is capable to adapt the model parameters to the specific situation (e.g. actual speakers, gain, acoustic channel, etc.) using only speech mixture data. Currently, source-specific data is required to learn the model. Inference in FHMMs is an essential ingredient for adaptation. We develop efficient approaches based on observation likelihood pruning. Both adaptation and efficient inference are empirically evaluated for the task of multipitch tracking using the GRID corpus.","PeriodicalId":55014,"journal":{"name":"IEEE Transactions on Audio Speech and Language Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TASL.2013.2260744","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62889678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Applying Multi- and Cross-Lingual Stochastic Phone Space Transformations to Non-Native Speech Recognition 多语言和跨语言随机电话空间变换在非母语语音识别中的应用

IEEE Transactions on Audio Speech and Language Processing Pub Date : 2013-08-01 DOI: 10.1109/TASL.2013.2260150

David Imseng, H. Bourlard, J. Dines, Philip N. Garner, M. Magimai.-Doss

{"title":"Applying Multi- and Cross-Lingual Stochastic Phone Space Transformations to Non-Native Speech Recognition","authors":"David Imseng, H. Bourlard, J. Dines, Philip N. Garner, M. Magimai.-Doss","doi":"10.1109/TASL.2013.2260150","DOIUrl":"https://doi.org/10.1109/TASL.2013.2260150","url":null,"abstract":"In the context of hybrid HMM/MLP Automatic Speech Recognition (ASR), this paper describes an investigation into a new type of stochastic phone space transformation, which maps “source” phone (or phone HMM state) posterior probabilities (as obtained at the output of a Multilayer Perceptron/MLP) into “destination” phone (HMM phone state) posterior probabilities. The resulting stochastic matrix transformation can be used within the same language to automatically adapt to different phone formats (e.g., IPA) or across languages. Additionally, as shown here, it can also be applied successfully to non-native speech recognition. In the same spirit as MLLR adaptation, or MLP adaptation, the approach proposed here is directly mapping posterior distributions, and is trained by optimizing on a small amount of adaptation data a Kullback-Leibler based cost function, along a modified version of an iterative EM algorithm. On a non-native English database (HIWIRE), and comparing with multiple setups (monophone and triphone mapping, MLLR adaptation) we show that the resulting posterior mapping yields state-of-the-art results using very limited amounts of adaptation data in mono-, cross- and multi-lingual setups. We also show that “universal” phone posteriors, trained on a large amount of multilingual data, can be transformed to English phone posteriors, resulting in an ASR system that significantly outperforms a system trained on English data only. Finally, we demonstrate that the proposed approach outperforms alternative data-driven, as well as a knowledge-based, mapping techniques.","PeriodicalId":55014,"journal":{"name":"IEEE Transactions on Audio Speech and Language Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TASL.2013.2260150","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62889096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Study of the General Kalman Filter for Echo Cancellation 用于回波抵消的通用卡尔曼滤波器的研究

IEEE Transactions on Audio Speech and Language Processing Pub Date : 2013-08-01 DOI: 10.1109/TASL.2013.2245654

C. Paleologu, J. Benesty, S. Ciochină

引用次数: 92

Effective Model Representation by Information Bottleneck Principle 基于信息瓶颈原理的有效模型表示

IEEE Transactions on Audio Speech and Language Processing Pub Date : 2013-08-01 DOI: 10.1109/TASL.2013.2253097

Ron M. Hecht, Elad Noor, Gil Dobry, Y. Zigel, Aharon Bar-Hillel, Naftali Tishby

引用次数: 4

Robust Log-Energy Estimation and its Dynamic Change Enhancement for In-car Speech Recognition 车载语音识别的鲁棒对数能量估计及其动态变化增强

IEEE Transactions on Audio Speech and Language Processing Pub Date : 2013-08-01 DOI: 10.1109/TASL.2013.2260151

Weifeng Li, Longbiao Wang, Yicong Zhou, H. Bourlard, Q. Liao

{"title":"Robust Log-Energy Estimation and its Dynamic Change Enhancement for In-car Speech Recognition","authors":"Weifeng Li, Longbiao Wang, Yicong Zhou, H. Bourlard, Q. Liao","doi":"10.1109/TASL.2013.2260151","DOIUrl":"https://doi.org/10.1109/TASL.2013.2260151","url":null,"abstract":"The log-energy parameter, typically derived from a full-band spectrum, is a critical feature commonly used in automatic speech recognition (ASR) systems. However, log-energy is difficult to estimate reliably in the presence of background noise. In this paper, we theoretically show that background noise affects the trajectories of not only the “conventional” log-energy, but also its delta parameters. This results in a poor estimation of the actual log-energy and its delta parameters, which no longer describe the speech signal. We thus propose a new method to estimate log-energy from a sub-band spectrum, followed by dynamic change enhancement and mean smoothing. We demonstrate the effectiveness of the proposed log-energy estimation and its post-processing steps through speech recognition experiments conducted on the in-car CENSREC-2 database. The proposed log-energy (together with its corresponding delta parameters) yields an average improvement of 32.8% compared with the baseline front-ends. Moreover, it is also shown that further improvement can be achieved by incorporating the new Mel-Frequency Cepstral Coefficients (MFCCs) obtained by non-linear spectral contrast stretching.","PeriodicalId":55014,"journal":{"name":"IEEE Transactions on Audio Speech and Language Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TASL.2013.2260151","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62888780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Joint Discriminative Decoding of Words and Semantic Tags for Spoken Language Understanding 词语和语义标签联合判别解码在口语理解中的应用

IEEE Transactions on Audio Speech and Language Processing Pub Date : 2013-08-01 DOI: 10.1109/TASL.2013.2256894

Anoop Deoras, Gökhan Tür, R. Sarikaya, Dilek Z. Hakkani-Tür

{"title":"Joint Discriminative Decoding of Words and Semantic Tags for Spoken Language Understanding","authors":"Anoop Deoras, Gökhan Tür, R. Sarikaya, Dilek Z. Hakkani-Tür","doi":"10.1109/TASL.2013.2256894","DOIUrl":"https://doi.org/10.1109/TASL.2013.2256894","url":null,"abstract":"Most Spoken Language Understanding (SLU) systems today employ a cascade approach, where the best hypothesis from Automatic Speech Recognizer (ASR) is fed into understanding modules such as slot sequence classifiers and intent detectors. The output of these modules is then further fed into downstream components such as interpreter and/or knowledge broker. These statistical models are usually trained individually to optimize the error rate of their respective output. In such approaches, errors from one module irreversibly propagates into other modules causing a serious degradation in the overall performance of the SLU system. Thus it is desirable to jointly optimize all the statistical models together. As a first step towards this, in this paper, we propose a joint decoding framework in which we predict the optimal word as well as slot sequence (semantic tag sequence) jointly given the input acoustic stream. Furthermore, the improved recognition output is then used for an utterance classification task, specifically, we focus on intent detection task. On a SLU task, we show 1.5% absolute reduction (7.6% relative reduction) in word error rate (WER) and 1.2% absolute improvement in F measure for slot prediction when compared to a very strong cascade baseline comprising of state-of-the-art large vocabulary ASR followed by conditional random field (CRF) based slot sequence tagger. Similarly, for intent detection, we show 1.2% absolute reduction (12% relative reduction) in classification error rate.","PeriodicalId":55014,"journal":{"name":"IEEE Transactions on Audio Speech and Language Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TASL.2013.2256894","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62888810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 20

Joint Source-Filter Optimization for Accurate Vocal Tract Estimation Using Differential Evolution 基于差分进化的声道精确估计联合源-滤波器优化

IEEE Transactions on Audio Speech and Language Processing Pub Date : 2013-08-01 DOI: 10.1109/TASL.2013.2255275

O. Schleusing, T. Kinnunen, B. Story, J. Vesin

{"title":"Joint Source-Filter Optimization for Accurate Vocal Tract Estimation Using Differential Evolution","authors":"O. Schleusing, T. Kinnunen, B. Story, J. Vesin","doi":"10.1109/TASL.2013.2255275","DOIUrl":"https://doi.org/10.1109/TASL.2013.2255275","url":null,"abstract":"In this work, we present a joint source-filter optimization approach for separating voiced speech into vocal tract (VT) and voice source components. The presented method is pitch-synchronous and thereby exhibits a high robustness against vocal jitter, shimmer and other glottal variations while covering various voice qualities. The voice source is modeled using the Liljencrants-Fant (LF) model, which is integrated into a time-varying auto-regressive speech production model with exogenous input (ARX). The non-convex optimization problem of finding the optimal model parameters is addressed by a heuristic, evolutionary optimization method called differential evolution. The optimization method is first validated in a series of experiments with synthetic speech. Estimated glottal source and VT parameters are the criteria used for comparison with the iterative adaptive inverse filter (IAIF) method and the linear prediction (LP) method under varying conditions such as jitter, fundamental frequency (f0) as well as environmental and glottal noise. The results show that the proposed method largely reduces the bias and standard deviation of estimated VT coefficients and glottal source parameters. Furthermore, the performance of the source-filter separation is evaluated in experiments using speech generated with a physical model of speech production. The proposed method reliably estimates glottal flow waveforms and lower formant frequencies. Results obtained for higher formant frequencies indicate that research on more accurate voice source models and their interaction with the VT is necessary to improve the source-filter separation. The proposed optimization approach promises to be a useful tool for future research addressing this topic.","PeriodicalId":55014,"journal":{"name":"IEEE Transactions on Audio Speech and Language Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TASL.2013.2255275","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62888566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

Analysis and Design of Multichannel Systems for Perceptual Sound Field Reconstruction 多通道感知声场重构系统的分析与设计

IEEE Transactions on Audio Speech and Language Processing Pub Date : 2013-08-01 DOI: 10.1109/TASL.2013.2260152

E. D. Sena, H. Hacıhabiboğlu, Z. Cvetković

{"title":"Analysis and Design of Multichannel Systems for Perceptual Sound Field Reconstruction","authors":"E. D. Sena, H. Hacıhabiboğlu, Z. Cvetković","doi":"10.1109/TASL.2013.2260152","DOIUrl":"https://doi.org/10.1109/TASL.2013.2260152","url":null,"abstract":"This paper presents a systematic framework for the analysis and design of circular multichannel surround sound systems. Objective analysis based on the concept of active intensity fields shows that for stable rendition of monochromatic plane waves it is beneficial to render each such wave by no more than two channels. Based on that finding, we propose a methodology for the design of circular microphone arrays, in the same configuration as the corresponding loudspeaker system, which aims to capture inter-channel time and intensity differences that ensure accurate rendition of the auditory perspective. The methodology is applicable to regular and irregular microphone/speaker layouts, and a wide range of microphone array radii, including the special case of coincident arrays which corresponds to intensity-based systems. Several design examples, involving first and higher-order microphones are presented. Results of formal listening tests suggest that the proposed design methodology achieves a performance comparable to prior art in the center of the loudspeaker array and a more graceful degradation away from the center.","PeriodicalId":55014,"journal":{"name":"IEEE Transactions on Audio Speech and Language Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TASL.2013.2260152","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62888920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 23

Musical Instrument Sound Morphing Guided by Perceptually Motivated Features 由感知动机特征引导的乐器声音变形

IEEE Transactions on Audio Speech and Language Processing Pub Date : 2013-08-01 DOI: 10.1109/TASL.2013.2260154

Marcelo F. Caetano, X. Rodet

{"title":"Musical Instrument Sound Morphing Guided by Perceptually Motivated Features","authors":"Marcelo F. Caetano, X. Rodet","doi":"10.1109/TASL.2013.2260154","DOIUrl":"https://doi.org/10.1109/TASL.2013.2260154","url":null,"abstract":"Sound morphing is a transformation that gradually blurs the distinction between the source and target sounds. For musical instrument sounds, the morph must operate across timbre dimensions to create the auditory illusion of hybrid musical instruments. The ultimate goal of sound morphing is to perform perceptually linear transitions, which requires an appropriate model to represent the sounds being morphed and an interpolation function to obtain intermediate sounds. Typically, morphing techniques directly interpolate the parameters of the sound model without considering the perceptual impact or evaluating the results. Perceptual evaluations are cumbersome and not always conclusive. In this work, we seek parameters of a sound model that favor linear variation of perceptually motivated temporal and spectral features used to guide the morph towards more perceptually linear results. The requirement of linear variation of feature values gives rise to objective evaluation criteria for sound morphing. We investigate several spectral envelope morphing techniques to determine which spectral representation renders the most linear transformation in the spectral shape feature domain. We found that interpolation of line spectral frequencies gives the most linear spectral envelope morphs. Analogously, we study temporal envelope morphing techniques and we concluded that interpolation of cepstral coefficients results in the most linear temporal envelope morph.","PeriodicalId":55014,"journal":{"name":"IEEE Transactions on Audio Speech and Language Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TASL.2013.2260154","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62889300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 23

Coding-Based Informed Source Separation: Nonnegative Tensor Factorization Approach 基于编码的信息源分离:非负张量分解方法

IEEE Transactions on Audio Speech and Language Processing Pub Date : 2013-08-01 DOI: 10.1109/TASL.2013.2260153

A. Ozerov, A. Liutkus, R. Badeau, G. Richard

{"title":"Coding-Based Informed Source Separation: Nonnegative Tensor Factorization Approach","authors":"A. Ozerov, A. Liutkus, R. Badeau, G. Richard","doi":"10.1109/TASL.2013.2260153","DOIUrl":"https://doi.org/10.1109/TASL.2013.2260153","url":null,"abstract":"Informed source separation (ISS) aims at reliably recovering sources from a mixture. To this purpose, it relies on the assumption that the original sources are available during an encoding stage. Given both sources and mixture, a side-information may be computed and transmitted along with the mixture, whereas the original sources are not available any longer. During a decoding stage, both mixture and side-information are processed to recover the sources. ISS is motivated by a number of specific applications including active listening and remixing of music, karaoke, audio gaming, etc. Most ISS techniques proposed so far rely on a source separation strategy and cannot achieve better results than oracle estimators. In this study, we introduce Coding-based ISS (CISS) and draw the connection between ISS and source coding. CISS amounts to encode the sources using not only a model as in source coding but also the observation of the mixture. This strategy has several advantages over conventional ISS methods. First, it can reach any quality, provided sufficient bandwidth is available as in source coding. Second, it makes use of the mixture in order to reduce the bitrate required to transmit the sources, as in classical ISS. Furthermore, we introduce Nonnegative Tensor Factorization as a very efficient model for CISS and report rate-distortion results that strongly outperform the state of the art.","PeriodicalId":55014,"journal":{"name":"IEEE Transactions on Audio Speech and Language Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TASL.2013.2260153","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62889642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 46