Recent Progress in Corpus-Based Spontaneous Speech Recognition(Feature Extraction and Acoustic Medelings, <Special Section>Corpus-Based Speech Technologies)
スポンサーリンク
概要
- 論文の詳細を見る
This paper overviews recent progress in the development of corpus-based spontaneous speech recognition technology. Although speech is in almost any situation spontaneous, recognition of spontaneous speech is an area which has only recently emerged in the field of automatic speech recognition. Broadening the application of speech recognition depends crucially on raising recognition performance for spontaneous speech. For this purpose, it is necessary to build large spontaneous speech corpora for constructing acoustic and language models. This paper focuses on various achievements of a Japanese 5-year national project "Spontaneous Speech: Corpus and Processing Technology" that has recently been completed. Because of various spontaneous-speech specific phenomena, such as filled pauses, repairs, hesitations, repetitions and disfluencies, recognition of spontaneous speech requires various new techniques. These new techniques include flexible acoustic modeling, sentence boundary detection, pronunciation modeling, acoustic as well as language model adaptation, and automatic summarization. Particularly automatic summarization including indexing, a process which extracts important and reliable parts of the automatic transcription, is expected to play an important role in building various speech archives, speech-based information retrieval systems, and human-computer dialogue systems.
- 社団法人電子情報通信学会の論文
- 2005-03-01
著者
関連論文
- Tree-Structured Clustering Methods for Piecewise Linear-Transformation-Based Noise Adaptation(Speech and Hearing)
- Recent Progress in Corpus-Based Spontaneous Speech Recognition(Feature Extraction and Acoustic Medelings, Corpus-Based Speech Technologies)
- THE USE OF FINITE-STATE TRANSDUCERS FOR MODELING PHONOLOGICAL AND MORPHOLOGICAL CONSTRAINTS IN AUTOMATIC SPEECH RECOGNITION
- Adaptation to Pronunciation Variations in Indonesian Spoken Query-Based Information Retrieval
- Committee-Based Active Learning for Speech Recognition
- Robust Gait-Based Person Identification against Walking Speed Variations
- Selected Topics from LVCSR Research for Asian Languages at Tokyo Tech
- Active Learning Using Phone-Error Distribution for Speech Modeling
- Distance-based Factor Graph Linearization and Sampled Max-sum Algorithm for Efficient 3D Potential Decoding of Macromolecules
- Active Learning Using Phone-Error Distribution for Speech Modeling