A hidden Markov model based visual speech synthesizer
نویسندگان
چکیده
This paper describes a hidden Markov model (HMM) based visual synthesizer designed to assist persons with impairedhearing. This synthesizer builds on results in the area of audio-visual speech recognition. We describe how a correlation HMM can be used to integrate independent acoustic and visual HMMs for speech-to-visual synthesis. Our results show that an HMM correlating model can signi cantly improve synchronization errors versus techniques which compensate for rate di erences through scaling.
منابع مشابه
HMM-based visual speech synthesis using dynamic visemes
In this paper we incorporate dynamic visemes into hidden Markov model (HMM)-based visual speech synthesis. Dynamic visemes represent intuitive visual gestures identified automatically by clustering purely visual speech parameters. They have the advantage of spanning multiple phones and so they capture the effects of visual coarticulation explicitly within the unit. The previous application of d...
متن کاملAn HMM-based speech-to-video synthesizer
Emerging broadband communication systems promise a future of multimedia telephony, e.g. the addition of visual information to telephone conversations. It is useful to consider the problem of generating the critical information useful for speechreading, based on existing narrowband communications systems used for speech. This paper focuses on the problem of synthesizing visual articulatory movem...
متن کاملSpeech enhancement based on hidden Markov model using sparse code shrinkage
This paper presents a new hidden Markov model-based (HMM-based) speech enhancement framework based on the independent component analysis (ICA). We propose analytical procedures for training clean speech and noise models by the Baum re-estimation algorithm and present a Maximum a posterior (MAP) estimator based on Laplace-Gaussian (for clean speech and noise respectively) combination in the HMM ...
متن کاملObjective and subjective feature evaluation for speaker-adaptive visual speech synthesis
This paper describes an evaluation of a feature extraction method for visual speech synthesis that is suitable for speaker-adaptive training of a Hidden Semi-Markov Model (HSMM)-based visual speech synthesizer. An audio-visual corpus from three speakers was recorded. While the features used for the auditory modality are well understood, we propose to use a standard Principal Component Analysis ...
متن کاملLow footprint High intelligibility Malay speech synthesizer based on Statistical Data
Speech synthesis plays a pivotal role nowadays. It can be found in various daily applications such as in mobile phones, navigation systems, languages learning software and so on. In this study, a Malay language speech synthesizer was designed using hidden Markov model to improve the performance of current Malay speech synthesizer and also extend Malay speech technology. Statistical parametric m...
متن کامل