Automatic phrasing is essential to Mandarin textto-speech synthesis. We select word format as target linguistic feature and propose an HMMbased approach to this issue. Then we define four states of prosodic positions for each word when employing a discrete hidden Markov model. The approach achieves high accuracy of roughly 82%, which is very close to that from manual labeling. Our experimental results also demonstrate that this approach has advantages over those part-ofspeech-based ones.
Traditional concatenative speech synthesis systems use a number of heuristics to deﬁne the target and concatenation costs, essential for the design of the unit selection component. In contrast to these approaches, we introduce a general statistical modeling framework for unit selection inspired by automatic speech recognition. Given appropriate data, techniques based on that framework can result in a more accurate unit selection, thereby improving the general quality of a speech synthesizer. They can also lead to a more modular and a substantially more efﬁcient system. ...
We present a component for incremental speech synthesis (iSS) and a set of applications that demonstrate its capabilities. This component can be used to increase the responsivity and naturalness of spoken interactive systems. While iSS can show its full strength in systems that generate output incrementally, we also discuss how even otherwise unchanged systems may proﬁt from its capabilities.
Windows 8 builds on this to allow applications to make use of speech Applications can speak messages using the Speech Synthesis feature Applications can be started and given commands Applications can accept commands using voice inpu
Speech Typically words are converted to phonemes in one of two ways: either by looking the words up in a dictionary (with possibly some limited morphological analysis), or by sounding the words out from their spelling using basic principles. • Dictionary Lookup • Letter to Sound Both appt~oaches have their advantages and disadvantages; dictionary lookup fails for unknown words (e.g., proper nouns) and letter to sound rules fail for irregular words, which are all too common in English.
This tutorial is about the evolution of speech technology from research to a mature industry. Today, spoken language communication with computers is becoming part of everyday life. Thousands of interactive applications using spoken language technology— known also as “conversational machines”—are only phone calls away, allowing millions of users each day to access information, perform transactions, and get help. Speech recognition, language understanding, text-to-speech synthesis, machine learning, and dialog management enabled this revolution after more than 50 years of research.
The detection of prosodic characteristics is an important aspect of both speech synthesis and speech recognition. Correct placement of pitch accents aids in more natural sounding speech, while automatic detection of accents can contribute to better wordlevel recognition and better textual understanding. In this paper we investigate probabilistic, contextual, and phonological factors that inﬂuence pitch accent placement in natural, conversational speech in a sequence labeling setting.
This paper is part of an MSc. report on a program called GENIE (Generator of Inflected English), written in CProlog, that acts as a front end to an existing speech synthesis program. It allows the user to type a sentence in English text, and then processes it so that the synthesiser will output it with natural-sounding inflection; that is, as well as transcribing text to a phonemic form that can be read by the system, it assigns this text an fO contour. The assigning of this stress is described in this paper, and it is asserted that the...
This paper pinpoints some of the problems faced when a computer text production model (COMMENTATOR) is to produce spontaneous speech, in speech. This paper discusses some of the problems in the light of the computer model of verbal production presented £n Sigurd (1982), Fornell (1983). For experimental purposes a simple speech synthesis device (VOTRAX) has been used. The Problem of producing naturally sounding utterances is also met in text-to-speech systems (see e.g. Carlson & Granstr~m, 1978). ...
Hidden Markov Models (HMMs), although known for decades, have made a big career nowadays and are still in state of development. This book presents theoretical issues and a variety of HMMs applications in speech recognition and synthesis, medicine, neurosciences, computational biology, bioinformatics, seismology, environment protection and engineering. I hope that the reader will find this book useful and helpful for their own research.
This book addresses different aspects of the research field and a wide range of topics in speech signal processing, speech recognition and language processing. The chapters are divided in three different sections: Speech Signal Modeling, Speech Recognition and Applications. The chapters in the first section cover some essential topics in speech signal processing used for building speech recognition as well as for speech synthesis systems: speech feature enhancement, speech feature vector dimensionality reduction, segmentation of speech frames into phonetic segments. ...
In the EMIME project we have studied unsupervised cross-lingual speaker adaptation. We have employed an HMM statistical framework for both speech recognition and synthesis which provides transformation mechanisms to adapt the synthesized voice in TTS (text-to-speech) using the recognized voice in ASR (automatic speech recognition). An important application for this research is personalised speech-to-speech translation that will use the voice of the speaker in the input language to utter the translated sentences in the output language. ...
This paper describes the latest version of speech-to-speech translation systems developed by the team of NICT-ATR for over twenty years. The system is now ready to be deployed for the travel domain. A new noise-suppression technique notably improves speech recognition performance. Corpus-based approaches of recognition, translation, and synthesis enable coverage of a wide variety of topics and portability to other languages. recent progress.
We will demonstrate the ModelTalker Voice Recorder (MT Voice Recorder) – an interface system that lets individuals record and bank a speech database for the creation of a synthetic voice. The system guides users through an automatic calibration process that sets pitch, amplitude, and silence. The system then prompts users with both visual (text-based) and auditory prompts. Each recording is screened for pitch, amplitude and pronunciation and users are given immediate feedback on the acceptability of each recording. ...
This paper presents a method for adapting a language generator to the strengths and weaknesses of a synthetic voice, thereby improving the naturalness of synthetic speech in a spoken language dialogue system. The method trains a discriminative reranker to select paraphrases that are predicted to sound natural when synthesized. The ranker is trained on realizer and synthesizer features in supervised fashion, using human judgements of synthetic voice quality on a sample of the paraphrases representative of the generator’s capability. ...
Cross-linguistic similarities are reﬂected by the speech sound systems of languages all over the world. In this work we try to model such similarities observed in the consonant inventories, through a complex bipartite network. We present a systematic study of some of the appealing features of these inventories with the help of the bipartite network. An important observation is that the occurrence of consonants follows a two regime power law distribution.
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Tổng hợp tiếng nói
Thành phần tổng hợp tiếng nói của một hệ thống TTS có chức năng tạo ra dạng sóng tiếng nói tương ứng với văn bản Dữ liệu vào thường là âm vị đã được chuyển đổi và ngữ âm tương ứng của câu nói. à ữâ ứ ủ â ói Ngoài ra, dữ liệu vào có thể gồm văn bản thô cùng với các thẻ đánh dấu để có chất lượng tiếng nói tốt hơn
Phân loại các hệ thống tổng hợp ạ ệ g g ợp tiếng nói
Các hệ thống tổng hợp tiếng nói gồm 3...
DWTs are constantly used to solve and treat more and more advanced problems. The
DWT algorithms were initially based on the compactly supported conjugate
quadrature filters (CQFs). However, a drawback in CQFs is due to the nonlinear phase
effects such as spatial dislocations in multi-scale analysis. This is avoided in
biorthogonal discrete wavelet transform (BDWT) algorithms, where the scaling and
wavelet filters are symmetric and linear phase. The biorthogonal filters are usually
constructed by a ladder-type network called lifting scheme.