This paper summarizes recent activities at LIMSI in multilingual speech recognition and its applications. While the main goal of speech recognition is to provide a transcription of the speech signal as a sequence of words, the same basic technology serves as the first step in other application areas, such as in automatic systems for information access and for automatic indexation of audiovisual...

This chapter examines the use of Automatic Speech Recognition (ASR) technology in the context of Computer Assisted Language Learning (CALL) and language learning and teaching research. A brief introduction to ASR is first provided, to make it clear why and how this technology can be used to the benefit of learning and development in second language (L2) spoken discourse. This is followed by an ...

This paper presents our group’s ongoing research in the area of computer-aided pronunciation training (CAPT) for Chinese learners of English. Our goal is to develop technologies in automatic speech recognition (ASR) to support productive training for learners. We focus on modeling possible errors due to negative transfer from L1 (i.e. Chinese) of Chinese learners to L2 (English). ASR techniques...

A simplified decoding method for the concept of REverberation MOdeling for Speech recognition (REMOS) [1] is proposed. In order to achieve robust distant-talking Automatic Speech Recognition (ASR), the REMOS concept uses a combination of clean-speech HMMs and a reverberation model to perform feature-domain dereverberation during decoding. The simplified decoding/dereverberation method proposed ...

This paper presents clustering experiments performed over noisy texts (i.e. texts that have been extracted through an automatic process like character or speech recognition). The effect of recognition errors is investigated by comparing clustering results performed over both clean (manually typed data) and noisy (automatic speech transcriptions) versions of the same speech recording corpus.

OBJECTIVE It has been the aim of the present study to introduce a novel automatic technique for the objective and quantitative assessment of speech intelligibility to the evaluation of postoperative outcome. PATIENTS AND METHODS Forty-six patients with oral carcinomas, mean age 59.8 +/- 10.1 years, and an age-matched control group of 40 subjects without oral diseases. Recordings of a standard...

Speech stream segregation is presented as a new speech enhancement for automatic speech recognition. Two issues are addressed: speech stream segregation from a mixture of sounds, and interfacing speech stream segregation with automatic speech recognition. Speech stream segregation is modeled as a process of extracting harmonic fragments, grouping these extracted harmonic fragments, and substitu...

Due to the advance of speech technologies and their increasing usage in various applications, automatic recognition of emotions in speech represents one of the emerging fields in human-computer interaction. This paper deals with several topics related to automatic emotional speech recognition, most notably with the improvement of recognition accuracy by lowering the dimensionality of the featur...

There is a great need for more TV programs to be closed-captioned to help hearing impaired and elderly people watch TV. For that purpose, automatic speech recognition is expected to contribute to providing text from speech in real-time. NHK has been using speech recognition for closed-captioning of some of its news, sports and other live TV programs. In news programs, automatic speech recogniti...

Speech has evolved as a primary form of communication between humans. The advent of digital technology, gave us highly versatile digital processors with high speed, low cost and high power which enable researchers to transform the analog speech signals in to digital speech signals that can be scientifically studied. Achieving higher recognition accuracy, low word error rate and addressing the i...