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This paper presents recent advances in Automatic Speech Recognition for the Czech Language. Improvements were achieved both in acoustic and language modeling. We mainly aim on the acoustic part of the issue. The results are presented in two contexts, the lecture recognition and SpeeCon+Temic test set. The paper shows the impact of using advanced modeling techniques such as HLDA, VTLN and CMLLR. On...
In this paper we present our recent efforts towards building a large vocabulary continuous speech recognizer for Tamil. We describe the text and speech corpus collected to realize this task. The data was complemented by a large amount of text data crawled from various Tamil news websites. The Tamil speech recognition system was bootstrapped using the Rapid Language Adaptation scheme which employs...
We believe that a benchmark evaluation is one of the key factors that help accelerate research and development of a Thai speech recognition system as various algorithms and training techniques can be systematically compared. In this paper, we are interested in benchmarking a general-domain Thai Large Vocabulary Continuous Speech Recognition (LVCSR) system using the LOTUS speech corpus. We conducted...
Speech recognition is becoming popular as a technology for the implementation of human interfaces. However, conventional approaches to large vocabulary continuous speech recognition (LVCSR) require a high performance CPU. In this paper, we describe a speech recognition system designed using a C-based architecture design methodology, which avoids this limitation. Application specific circuits such...
In the field of speech recognition, performance varies much when the system is trained or tested with different data. In this paper, we explore the effect of training and test data on the performance of automatic speech recognition systems. Unlike other researchers who analyze the effect of training and testing as pattern learning and recognition of vectors, the effect of data is investigated as effect...
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