Beyond English text: Multilingual and multimedia information retrieval.

Non

放送ニュースの自動音声認識とインデクシングに関する研究

制度:新 ; 文部省報告番号:乙2056号 ; 学位の種類:博士(工学) ; 授与年月日:2006/12/21 ; 早大学位記番号:新435

Spoken content retrieval: A survey of techniques and technologies

Speech media, that is, digital audio and video containing spoken content, has blossomed in recent years. Large collections are accruing on the Internet as well as in private and enterprise settings. This growth has motivated extensive research on techniques and technologies that facilitate reliable indexing and retrieval. Spoken content retrieval (SCR) requires the combination of audio and speech processing technologies with methods from information retrieval (IR). SCR research initially investigated planned speech structured in document-like units, but has subsequently shifted focus to more informal spoken content produced spontaneously, outside of the studio and in conversational settings. This survey provides an overview of the field of SCR encompassing component technologies, the relationship of SCR to text IR and automatic speech recognition and user interaction issues. It is aimed at researchers with backgrounds in speech technology or IR who are seeking deeper insight on how these fields are integrated to support research and development, thus addressing the core challenges of SCR

Automatsko raspoznavanje hrvatskoga govora velikoga vokabulara

This paper presents procedures used for development of a Croatian large vocabulary automatic speech recognition system (LVASR). The proposed acoustic model is based on context-dependent triphone hidden Markov models and Croatian phonetic rules. Different acoustic and language models, developed using a large collection of Croatian speech, are discussed and compared. The paper proposes the best feature vectors and acoustic modeling procedures using which lowest word error rates for Croatian speech are achieved. In addition, Croatian language modeling procedures are evaluated and adopted for speaker independent spontaneous speech recognition. Presented experiments and results show that the proposed approach for automatic speech recognition using context-dependent acoustic modeling based on Croatian phonetic rules and a parameter tying procedure can be used for efficient Croatian large vocabulary speech recognition with word error rates below 5%.Članak prikazuje postupke akustičkog i jezičnog modeliranja sustava za automatsko raspoznavanje hrvatskoga govora velikoga vokabulara. Predloženi akustički modeli su zasnovani na kontekstno-ovisnim skrivenim Markovljevim modelima trifona i hrvatskim fonetskim pravilima. Na hrvatskome govoru prikupljenom u korpusu su ocjenjeni i uspoređeni različiti akustički i jezični modeli. U članku su uspoređ eni i predloženi postupci za izračun vektora značajki za akustičko modeliranje kao i sam pristup akustičkome modeliranju hrvatskoga govora s kojim je postignuta najmanja mjera pogrešno raspoznatih riječi. Predstavljeni su rezultati raspoznavanja spontanog hrvatskog govora neovisni o govorniku. Postignuti rezultati eksperimenata s mjerom pogreške ispod 5% ukazuju na primjerenost predloženih postupaka za automatsko raspoznavanje hrvatskoga govora velikoga vokabulara pomoću vezanih kontekstnoovisnih akustičkih modela na osnovu hrvatskih fonetskih pravila

An Automatic Real-time Synchronization of Live speech with Its Transcription Approach

Most studies in automatic synchronization of speech and transcription focus on the synchronization at the sentence level or the phrase level. Nevertheless, in some languages, like Thai, boundaries of such levels are difficult to linguistically define, especially in case of the synchronization of speech and its transcription. Consequently, the synchronization at a finer level like the syllabic level is promising. In this article, an approach to synchronize live speech with its corresponding transcription in real time at the syllabic level is proposed. Our approach employs the modified real-time syllable detection procedure from our previous work and the transcription verification procedure then adopts to verify correctness and to recover errors caused by the real-time syllable detection procedure. In experiments, the acoustic features and the parameters are customized empirically. Results are compared with two baselines which have been applied to the Thai scenario. Experimental results indicate that, our approach outperforms two baselines with error rate reduction of 75.9% and 41.9% respectively and also can provide results in the real-time situation. Besides, our approach is applied to the practical application, namely ChulaDAISY. Practical experiments show that ChulaDAISY applied with our approach could reduce time consumption for producing audio books

Spartan Daily, November 15, 1977

Volume 69, Issue 52https://scholarworks.sjsu.edu/spartandaily/6273/thumbnail.jp

A pipeline for the creation of multimodal corpora from YouTube videos

This paper introduces an open-source pipeline for the creation of multimodal corpora from YouTube videos. It minimizes storage and bandwidth requirements, because the videos themselves need not be downloaded and can remain on YouTube’s servers. It also minimizes processing requirements by using YouTube’s automatically generated subtitles, thus avoiding a computationally expensive automatic speech recognition processing step. The pipeline combines standard tools and provides as its output a corpus file in the industry-standard vertical format used by many corpus managers. It is straightforwardly extensible with the addition of further levels of annotation and can be adapted to languages other than English