Browsing by Author "Chen, Sin-Horng"

Now showing 1 - 20 of 50

A Hakka text-to-speech system
(2006)
Yu, Hsiu-Min
;
Hwang, Hsin-Te
;
Lin, Dong-Yi
;
Chen, Sin-Horng
;
電信工程研究所
In this paper, the implementation of a Hakka text-to-speech (TIS) system is presented. The system is designed based on the same principle of developing a Mandarin and a Min-Nan TTS systems proposed previously. It takes 671 base-syllables as basic synthesis units and uses a recurrent neural network (RNN)-based prosody generator to generate proper prosodic parameters for synthesizing natural output speech. The whole system is implemented by software and runs in real-time on PC. Informal subjective listening test confirmed that the system performed well. All synthetic speeches sounded well for well-tokenized texts and fair for texts with automatic tokenization.
A Lattice-Reduction Aided List Demapper for Coded MIMO Receiver
(2013)
Hsieh, Tung-Jung
;
Sheen, Wern-Ho
;
Chen, Sin-Horng
;
Hsu, Jen-Yuan
;
資訊工程學系
The max-log list demapper has been widely employed in the implementations of a coded multiple-input multiple-output (MIMO) receiver, where only a candidate-list of signal vectors is examined in the likelihood-ratio calculation to reduce complexity. Traditionally, the candidate-list is generated in the original-lattice domain which, unfortunately, results in a severe degradation in the performance of demapper if the channel is in ill-condition. In this paper, a new lattice-reduction aided max-log list demapper is proposed in which the candidate-list is generated after a successive cancellation of multi-layer interference in the lattice-reduced domain. Thanks to the newly designed metrics and search algorithms for the generation of the candidate-list, the proposed demapper provides significant gains over the existing methods, especially for the cases with a small list size and/or under a spatially-correlated channel.
A Lattice-Reduction Aided Max-Log List Demapper for Iterative Coded MIMO Receiver
(2014-01-01)
Hsieh, Tung-Jung
;
Sheen, Wern-Ho
;
Chen, Sin-Horng
;
Hsu, Jen-Yuan
;
資訊工程學系
The max-log list demapper has been widely employed in the implementation of a coded multiple-input multiple-output (MIMO) receiver, where only a candidate-list of signal vectors is examined in the likelihood-ratio calculation to reduce complexity. Traditionally, the candidate-list is generated in the original-lattice domain which, unfortunately, results in a severe degradation in the performance of demapper if the channel is in ill-condition. In this paper, a new lattice-reduction aided max-log list demapper is proposed for iterative receivers in which the candidate-list is generated after a successive cancellation of multi-layer interference in the lattice-reduced domain. Thanks to the newly designed metric and search algorithm for the generation of the candidate-list, the proposed demapper provides significant gains over the existing methods, especially for the cases with a small list size and/or under a spatially-correlated channel. The prior information coming out of the decoder is also exploited to lower the complexity of the demapper.
A New Approach of Speaking Rate Modeling for Mandarin Speech Prosody
(2012)
Hsieh, Chiao-Hua
;
Chiang, Chen-Yu
;
Wang, Yih-Ru
;
Yu, Hsiu-Min
;
Chen, Sin-Horng
A new approach of Mandarin-speech prosody modeling to consider the effects of speaking rate is proposed. The approach is a modification of our previous prosody labeling and modeling method to take speaking rate as a continuous independent variable and let prosodic-acoustic features and some parameters of prosodic models depend on it in order to count its influences. A speaking rate-dependent hierarchical prosodic model is hence constructed from four speech corpora of a single female speaker with fast, normal, medium and slow speaking rates. An analysis of the effects of speaking rate on the model parameters showed that they agreed well with our prior knowledge. So, the proposed approach provides a systematic and effective way to quantify the effects of speaking rate on Mandarin-speech prosody.
A New Model-based Prosody Coder for Mandarin Speech
(2013)
Chiang, Chen-Yu
;
Hung, Yu-Ping
;
Chen, Sin-Horng
;
Wang, Yih-Ru
;
電機工程學系
In this paper, a novel parametric prosody coding approach for Mandarin speech is proposed. It employs a hierarchical prosodic model (HPM) as a prosody generating model in the encoder to analyze the speech prosody of the input utterance to obtain a parametric representation of four prosodic-acoustic features of syllable pitch contour, syllable duration, syllable energy level, and syllable-juncture pause duration for encoding. In the decoder, the four prosodic-acoustic features are reconstructed by a synthesis operation using the decoded HPM parameters. The reconstructed prosodic features are lastly used in an HMM-based speech synthesizer to help to generate the reconstructed speech. Experimental results show that the reconstructed speech has good quality at low data rates of 114.9 bits/s for a speaker-dependent task. An informal listening test confirmed decoded speeches sounded very fluently.
A New Prosody-Assisted Mandarin ASR System
(2012-08-01)
Chen, Sin-Horng
;
Yang, Jyh-Her
;
Chiang, Chen-Yu
;
Liu, Ming-Chieh
;
Wang, Yih-Ru
This paper presents a new prosody-assisted automatic speech recognition (ASR) system for Mandarin speech. It differs from the conventional approach of using simple prosodic cues on employing a sophisticated prosody modeling approach based on a four-layer prosody-hierarchy structure to automatically generate 12 prosodic models from a large unlabeled speech database by the joint prosody labeling and modeling (PLM) algorithm proposed previously. By incorporating these 12 prosodic models into a two-stage ASR system to rescore the word lattice generated in the first stage by the conventional hidden Markov model (HMM) recognizer, we can obtain a better recognized word string. Besides, some other information can also be decoded, including part of speech (POS), punctuation mark (PM), and two types of prosodic tags which can be used to construct the prosody-hierarchy structure of the testing speech. Experimental results on the TCC300 database, which consists of long paragraphic utterances, showed that the proposed system significantly outperformed the baseline scheme using an HMM recognizer with a factored language model which models word, POS, and PM. Performances of 20.7%, 14.4%, and 9.6% in word, character, and base-syllable error rates were obtained. They corresponded to 3.7%, 3.7%, and 2.4% absolute (or 15.2%, 20.4%, and 20% relative) error reductions. By an error analysis, we found that many word segmentation errors and tone recognition errors were corrected.
A Novel Model-based Pitch Conversion Method for Mandarin Speech
(2009)
Hwang, Hsin-Te
;
Chiang, Chen-Yu
;
Sung, Po-Yi
;
Chen, Sin-Horng
;
電信工程研究所
In this paper, a novel model-based pitch conversion method for Mandarin is presented and compared with other two conventional conversion methods, i.e. the mean/variance transformation approach and the GMM-based mapping approach. Syllable pitch contour is first quantized by 3(rd) order orthogonal expansion coefficients; then, the source and target speakers' prosodic models are constructed, respectively. Two mapping methods based on the prosodic model are presented. Objective tests confirmed that one of the proposed methods are superior the conventional methods. Some findings in informal listening tests and objective tests are worthwhile to further investigate.
A Probabilistic Interpretation for Artificial Neural Network-based Voice Conversion
(2015)
Hwang, Hsin-Te
;
Tsao, Yu
;
Wang, Hsin-Min
;
Wang, Yih-Ru
;
Chen, Sin-Horng
Voice conversion (VC) using artificial neural networks (ANNs) has shown its capability to produce better sound quality of the converted speech than that using Gaussian mixture model (GMM). Although ANN-based VC works reasonably well, there is still room for further improvement. One of the promising ways is to adopt the successful techniques in statistical model-based parameter generation (SMPG), such as trajectory-based mapping approaches that are originally designed for GMM-based VC and hidden Markov model (HMM)-based speech synthesis. This study presents a probabilistic interpretation for ANN-based VC. In this way, ANN-based VC can easily incorporate the successful techniques in SMPG. Experimental results demonstrate that the performance of ANN-based VC can be effectively improved by two trajectory-based mapping techniques (maximum likelihood parameter generation (MLPG) algorithm and maximum likelihood-based trajectory mapping considering global variance (referred to as MLGV)), compared to the conventional ANN-based VC with frame-based mapping and the GMM-based VC with the MLPG algorithm. Moreover, ANN-based VC with the trajectory-based mapping techniques can achieve comparable performance when compared to the state-of-the-art GMM-based VC with the MLGV algorithm.
A SPEAKING RATE-CONTROLLED MANDARIN TTS SYSTEM
(2013)
Hsieh, Chiao-Hua
;
Wang, Yih-Ru
;
Chiang, Chen-Yu
;
Chen, Sin-Horng
;
電子工程學系及電子研究所
In this paper, a new speaking rate-controlled Mandarin TTS system based on a speaking rate-dependent hierarchical prosodic model (SR-HPM) [6] is proposed. In the training phase, a data-driven approach is employed to automatically build the SR-HPM directly from a large prosody-unlabeled speech database containing utterances of various speaking rates. The SR-HPM comprises 15 sub-models designed to describe various relationships among 3 types of prosodic-acoustic features of speech utterances, two types of prosodic tags specifying a 4-layer prosody hierarchy, linguistic features of various levels of the associated texts, and the speaking rates. In the test phase, the SR-HPM is employed to generate 4 prosodic-acoustic features, including syllable pitch contours, syllable durations, syllable energy levels, and syllable juncture pause durations. Combining these prosodic features with the spectral features generated by the HTS synthesizer, the system can generate natural speech for any speaking rate in a wide range of 0.15-0.3 seconds/syllable. A distinct feature of the system to control the occurrence frequencies of breaks of various types as well as their pause durations according to the given speaking rate was demonstrated. A subjective test showed that MOS scores of 3.35, 3.44 and 3.28 were achieved respectively for fast (SR= 0.17 sec/syllable), medium (SR=0.2 sec/syllable) and slow (SR= 0.25 sec/syllable) synthetic speeches.
A Study of Mutual Information for GMM-Based Spectral Conversion
(2012)
Hwang, Hsin-Te
;
Tsao, Yu
;
Wang, Hsin-Min
;
Wang, Yih-Ru
;
Chen, Sin-Horng
The Gaussian mixture model (GMM)-based method has dominated the field of voice conversion (VC) for last decade. However, the converted spectra are excessively smoothed and thus produce muffled converted sound. In this study, we improve the speech quality by enhancing the dependency between the source (natural sound) and converted feature vectors (converted sound). It is believed that enhancing this dependency can make the converted sound closer to the natural sound. To this end, we propose an integrated maximum a posteriori and mutual information (MAPMI) criterion for parameter generation on spectral conversion. Experimental results demonstrate that the quality of converted speech by the proposed MAPMI method outperforms that by the conventional method in terms of formal listening test.
A STUDY ON CROSS-LANGUAGE KNOWLEDGE INTEGRATION IN MANDARIN LVCSR
(2012)
Chiang, Chen-Yu
;
Siniscalchi, Sabato Marco
;
Wang, Yih-Ru
;
Chen, Sin-Horng
;
Lee, Chin-Hui
We present a cross-language knowledge integration framework to improve the performance in large vocabulary continuous speech recognition. Two types of knowledge sources, manner attribute and prosodic structure, are incorporated. For manner of articulation, cross-lingual attribute detectors trained with an American English corpus (WSJ0) are utilized to verify and rescore hypothesized Mandarin syllables in word lattices obtained with state-of-the-art systems. For the prosodic structure, models trained with an unsupervised joint prosody labeling and modeling technique using a Mandarin corpus (TCC300) are used in lattice rescoring. Experimental results on Mandarin syllable, character and word recognition with the TCC300 corpus show that the proposed approach significantly outperforms the baseline system that does not use articulatory and prosodic information. It also demonstrates a potential of utilizing results from cross-lingual attribute detectors as a language-universal frontend for automatic speech recognition.
A SYLLABLE-BASED PROSODY MODELING FOR L1 AND L2 ENGLISH SPEECHES
(2012)
Chen, Wei-Fan
;
Kuo, Chin-Kuan
;
Wang, Yih-Ru
;
Chen, Sin-Horng
;
電機工程學系
In this paper, a statistical prosody modeling approach for L1 and L2 English speeches is proposed. The study focuses on the modeling of two prosodic-acoustic features: syllable duration and log-pitch contour. Several major affecting factors (AFs) that influence the variations of these two features are considered. They include lexical stress, word length, nearby break type, phonemic constituent of syllable, and prosodic state. A sequential optimization procedure is adopted to automatically train the two models from the TWNAESOP corpus recorded in Taiwan. Experimental results showed that most AFs estimated agreed well with our prior linguistic knowledge. The differences in the prosody of L1 and L2 speeches were also explored.
Advanced Metering the Signal Activity of Combined Signal in Sparse Data Condition
(2011)
Lo, Wen-Hui
;
Chen, Sin-Horng
;
電信工程研究所
;
Institute of Communications Engineering
The performance of finding the upper bound of eigenvalues (UBE) is affected by the quality of correlation matrix estimation. In this paper, a new quantile-based maximum likelihood mean estimator is proposed to improve the mean estimation on sparse data condition so as to obtain a more reliable correlation matrix estimate from observed samples. This in turn improves the UBE finding. The study is specially focused on the quasi-normal signal of combined quantities with asymptotic window-shape distribution and fast-decaying short tail. Experimental results show that the new mean estimator outperforms the conventional sample mean estimator on mean estimation. The UBE finding is also improved accordingly.
Advanced Unsupervised Joint Prosody Labeling and Modeling for Mandarin Speech and Its Application to Prosody Generation for TTS
(2009)
Chiang, Chen-Yu
;
Chen, Sin-Horng
;
Wang, Yih-Ru
;
電信工程研究所
;
Institute of Communications Engineering
Motivated by the success of the unsupervised joint prosody labeling and modeling (UJPLM) method for Mandarin speech on modeling of syllable pitch contour in our previous study, in this paper, the advanced UJPLM (A-UJPLM) method is proposed based on UJPLM to jointly label prosodic tags and model syllable pitch contour, duration and energy level. Experimental results on the Sinica Treebank corpus showed that most prosodic tags labeled were linguistically meaningful and the model parameters estimated were interpretable and generally agreed with other previous study. In virtue of the functions given by the model parameters, an application of A-UJPLM to the prosody generation for Mandarin TTS is proposed. Experimental results showed that the proposed method performed well. Most predicted prosodic features matched well to their original counterparts. This also reconfirmed the effectiveness of the A-UJPLM method.
Alleviating the Over-Smoothing Problem in GMM-Based Voice Conversion with Discriminative Training
(2013-01-01)
Hwang, Hsin-Te
;
Tsao, Yu
;
Wang, Hsin-Min
;
Wang, Yih-Ru
;
Chen, Sin-Horng
In this paper, we propose a discriminative training (DT) method to alleviate the muffled sound effect caused by over smoothing in the Gaussian mixture model (GMM)-based voice conversion (VC). For the conventional GMM-based VC, we often observed a large degree of ambiguities among acoustic classes (generative classes), determined by the source feature vectors for generating the converted feature vectors, causing the "muffled sound" effect on the converted voice. The proposed DT method is applied to refine the parameters in the maximum likelihood (ML)-trained joint density GMM (JDGMM) in the training stage to reduce the ambiguities among acoustic classes (generative classes) to alleviate the muffled sound effect. Experimental results demonstrate that the DT method significantly enhances the discriminative power between acoustic classes (generative classes) in the objective evaluation and effectively alleviates the muffled sound effect in the subjective evaluation.
An Automatic Prosody Labeling Method for Mandarin Speech
(2007)
Chiang, Chen-Yu
;
Yu, Hsiu-Min
;
Wang, Yih-Ru
;
Chen, Sin-Horng
;
電信工程研究所
A new model-based automatic prosody labeling method for Mandarin speech is proposed. It first introduces four models to describe the relationships of the prosody tags to be labeled, the prosodic features of the speech signals, and the linguistic features of the associated texts. It then employs a sequential optimization procedure to estimate parameters of these four models and find all prosody tags. Experimental results on the Sinica Tree-Bank corpus showed that most prosody tags labeled were meaningful and the estimated parameters of these four models matched well with our a priori knowledge about Mandarin prosody.
An Exploration of Local Speaking Rate Variations in Mandarin Read Speech
(2018-01-01)
Liou, Guan-Tin
;
Chiang, Chen-Yu
;
Wang, Yih-Ru
;
Chen, Sin-Horng
;
電機工程學系
This paper explores speaking rate variation in Mandarin read speech. In contrast to assuming that each utterance is generated in a constant or global speaking rate, this study seeks to estimate local speaking rate for each prosodic unit in an utterance. The exploration is based on the existing speaking rate-dependent hierarchical prosodic model (SR-HPM). The main idea is to first use the SR-HPM to explore the prosodic structures of utterances and extract the prosodic units. Then, local speaking rate is estimated for each prosodic unit (prosodic phrase in this study). Some major influence factors including tone, base syllable type, prosodic structure, and speaking rate of the higher prosodic units (utterance and BG/PG) are compensated in the local SR estimation. A syntactic-local SR model is constructed and use in the prosody generation of Mandarin TTS. Experimental results on a large read speech corpus generated by a professional female announcer showed that the generated prosody with local speaking rate variations is proved to be more vivid than the one with a constant speaking rate.
An Investigation on the Mandarin Prosody of a Parallel Multi-Speaking Rate Speech Corpus
(2009)
Chiang, Chen-Yu
;
Tang, Cheng-Chang
;
Yu, Hsiu-Min
;
Wang, Yih-Ru
;
Chen, Sin-Horng
In this paper, the prosody of a parallel multi-speaking rate Mandarin read speech corpus is investigated. The corpus contains four parallel speech datasets uttered by a female professional announcer with various speech rates (SRs) of 4.40 (fast), 3.82 (normal), 2.97 (median) and 2.45 (slow) syllables/second. By using the unsupervised joint prosody labeling and modeling (PLM) method proposed previously, the relationship between SR and various prosodic features, including pause duration, patterns of three high-level prosodic constituents, and the break labels, are investigated. The analyses reported in this study could be very informative in developing prosody generation mechanism for text-to-speech and prosody modeling for automatic speech recognition in various SRs.
An SVD-aided List Demapper for Iterative Coded-MIMO Receivers
(2014-01-01)
Hsieh, Tung-Jung
;
Sheen, Wern-Ho
;
Chen, Sin-Horng
;
Hsu, Jen-Yuan
;
資訊工程學系
The list demapper has been widely implemented in a coded multiple-input multiple-output (MIMO) receiver, where only a part of total signal vectors are examined in the calculation of likelihood ratio for low complexity. Generally, the list is generated either in the original or the lattice-reduced domain. In the latter, thanks to the operation of lattice reduction (LR), a better-conditioned MIMO channel is obtained, and the adverse effect of noise enhancement is mitigated in the generation of list and thus can achieve a better performance. In this paper, a new singular-value-decomposition (SVD)-aided list demapper is proposed for the iterative coded-MIMO receiver. With SVD, the layer interference incurred in the operation of LR can be avoided, and that renders the SVD-aided list demapper a lower complexity. Computer simulations have confirmed that the proposed demapper has better performance-complexity tradeoffs as compared to the best-performed LR-aided methods in the literature.
Discriminative Analysis of Distortion Sequences in Speech Recognition
(1993-07-01)
Chang, Pao-Chung
;
Chen, Sin-Horng
;
Juang, Biing-Hwang
;
電信工程研究所
;
Institute of Communications Engineering
In a traditional speech recognition system, the distance score between a test token and a reference pattern is obtained by simply averaging the distortion sequence resulted from matching of the two patterns through a dynamic programming procedure. The final decision is made by choosing the one with the minimal average distance score. If we view the distortion sequence as a form of observed features, a decision rule based on a specific discriminant function designed for the distortion sequence obviously will perform better than that based on the simple average distortion. We, therefore, suggest in this paper a linear discriminant function of the form Delta = Sigma(T)(i=1) omega(i) * d(i) to compute the distance score A instead of a direct average Delta = 1/T Sigma(T)(i=1) d(i). Several adaptive algorithms are proposed to learn the discriminant weighting function in this paper. These include one heuristic method, two methods based on the error propagation algorithm [1], [2], and one method based on the generalized Probabilistic descent (GPD) algorithm [3]. We study these methods in a speaker-independent speech recognition task involving utterances of the highly confusible English E-set (b, c, d, e, g, p, t, v, z). The results show that the best performance is obtained by using the GPD method which achieved a 78.1% accuracy, compared to 67.6% with the traditional unweighted average method. Besides the experimental comparisons, an analytical discussion of various training algorithms is also provided.