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In this paper, we give an overview of the AMIDA systems for transcription of conference and lecture room meetings. The systems were developed for participation in the Rich Transcription evaluations conducted by the National Institute for Standards and Technology in the years 2007 and 2009 and can process close talking and far field microphone recordings.(More)
This paper describes the AMI transcription system for speech in meetings developed in collaboration by five research groups. The system includes generic techniques such as discriminative and speaker adaptive training, vocal tract length normalisation, heteroscedastic linear discriminant analysis, maximum likelihood linear regression, and phone posterior(More)
In this paper we describe the 2005 AMI system for the transcription of speech in meetings used in the 2005 NIST RT evaluations. The system was designed for participation in the speech to text part of the evaluations, in particular for transcription of speech recorded with multiple distant microphones and independent headset microphones. System performance(More)
This paper discusses the evaluation of automatic speech recognition (ASR) systems developed for practical applications, suggesting a set of criteria for application-oriented performance measures. The commonly used word error rate (WER), which poses ASR evaluation as a string editing process, is shown to have a number of limitations with respect to these(More)
A major component in the development of any speech recognition system is the decoder. As task complexities and, consequently, system complexities have continued to increase the decoding problem has become an increasingly significant component in the overall speech recognition system development effort, with efficient decoder design contributing to(More)
In conventional speech synthesis, large amounts of phonetically balanced speech data recorded in highly controlled recording studio environments are typically required to build a voice. Although using such data is a straightforward solution for high quality synthesis, the number of voices available will always be limited, because recording costs are high.(More)
We present the AMI 2006 system for the transcription of speech in meetings. The system was jointly developed by multiple sites on the basis of the 2005 system for participation in the NIST RT'05 evaluations. The paper describes major developments such as improvements in automatic segmentation, cross-domain model adaptation, inclusion of MLP based features,(More)
The AMI(DA) system is a meeting room speech recognition system that has been developed and evaluated in the context of the NIST Rich Text (RT) evaluations. Recently, the " Distant Access " requirements of the AMIDA project have necessitated that the system operate in real-time. Another more difficult requirement is that the system fit into a live meeting(More)
The EMIME European project is conducting research in the development of technologies for mobile, personalized speech-to-speech translation systems. The hidden Markov model (HMM) is being used as the underlying technology in both automatic speech recognition (ASR) and text-to-speech synthesis (TTS) components; thus, the investigation of unified statistical(More)
The advent of statistical speech synthesis has enabled the unification of the basic techniques used in speech synthesis and recognition. Adaptation techniques that have been successfully used in recognition systems can now be applied to synthesis systems to improve the quality of the synthesized speech. The application of vocal tract length normalization(More)