Audio-Visual Isolated Words Recognition for Voice Dialogue System
نویسنده
چکیده
This contribution is about experiments in audio-visual isolated words recognition. The results of these experiments will be used to improve our voice dialogue system, where visual speech recognition will be added. The voice dialogue systems can be used in train or bus stations (or elsewhere), where noise levels are relatively high, therefore the visual part of speech can improve the recognition rate mainly in noisy conditions. The audio-visual recognition of isolated words in our experiments was based on the technique of two-stream Hidden Markov Models (HMM) and on the HMM of single Czech phonemes and visemes. Different visual speech features and a different number of states and mixtures of HMM were evaluated in single tests. In the following experiments, isolated words were being recognized after training of the HMM and babble noise was added in the successive steps to the acoustic speech signal.
منابع مشابه
Recognition of isolated words using Zernike and MFCC features for audio visual speech recognition
Automatic Speech Recognition (ASR) by machine is an attractive research topic in signal processing domain and has attracted many researchers to contribute in this area. In recent year, there have been many advances in automatic speech reading system with the inclusion of audio and visual speech features to recognize words under noisy conditions. The objective of audio-visual speech recognition ...
متن کاملAn Improvement in Audio-Visual Voice Activity Detection for Automatic Speech Recognition
Noise-robust Automatic Speech Recognition (ASR) is essential for robots which are expected to communicate with humans in a daily environment. In such an environment, Voice Activity Detection (VAD) strongly affects the performance of ASR because there are many acoustically and visually noises. In this paper, we improved Audio-Visual VAD for our two-layered audio visual integration framework for ...
متن کاملA robust audio-visual speech recognition using audio-visual voice activity detection
This paper proposes a novel speech recognition method combining Audio-Visual Voice Activity Detection (AVVAD) and Audio-Visual Automatic Speech Recognition (AVASR). AVASR has been developed to enhance the robustness of ASR in noisy environments, using visual information in addition to acoustic features. Similarly, AVVAD increases the precision of VAD in noisy conditions, which detects presence ...
متن کاملMultifactor Fusion for Audio-Visual Speaker Recognition
In this paper we propose a multifactor hybrid fusion approach for enhancing security in audio-visual speaker verification. Speaker verification experiments conducted on two audiovisual databases, VidTIMIT and UCBN, show that multifactor hybrid fusion involve a combination feature-level fusion of lip-voice features and face-lip-voice features at score-level is indeed a powerful technique for spe...
متن کاملCharacteristics of the Use of Coupled Hidden Markov Models for Audio-Visual Polish Speech Recognition
This paper focuses on combining audio-visual signals for Polish speech recognition in conditions of highly disturbed audio speech signal. Recognition of audio-visual speech was based on combined hidden Markov models (CHMM). Described methods where developed for a single isolated command, nevertheless their effectiveness indicated that they would also work similarly in continuous audio-visual sp...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2010