State-of-the-art ASR systems typically use phoneme as the subword units. In this paper, we investigate a system where the word models are defined in-terms of two different sub-word units, i.e., phonemes and graphemes. We train models for both the subword units, and then perform decoding using either both or just one subword unit. We have studied this system for American English language where there is weak correspondence between the grapheme and phoneme. The results from our studies show that there is good potential in using grapheme as auxiliary subword units. 1
This paper compares the recognition accuracy of a phoneme-based automatic speech recognition system ...
Schillo C, Fink GA, Kummert F. Grapheme based speech recognition for large vocabularies. In: Intern...
In this paper, we describe a method to enhance the readability of the textual output of a large voca...
submitted for publication Abstract. Standard ASR systems typically use phoneme as the subword units....
In this paper we present a study of automatic speech recognition systems using context-dependent pho...
tems are based on modelling acoustic sub-word units such as phonemes. Phonemisation dictionaries and...
There is growing interest in using graphemes as subword units, especially in the context of the rapi...
The state-of-the-art automatic speech recognition (ASR) systems typically use phonemes as subword un...
Large vocabulary speech recognition systems traditionally represent words in terms of smaller subwor...
In today's society, speech recognition systems have reached a mass audience, especially in the field...
Standard hidden Markov model (HMM) based automatic speech recogni-tion (ASR) systems use phonemes as...
Standard hidden Markov model (HMM) based automatic speech recognition (ASR) systems use phonemes as ...
There is growing interest in using graphemes as subword units, especially in the context of the rapi...
We present a framework for discovering acoustic units and generating an associated pronunciation lex...
Automatic SpeechRecognition (ASR) systems that have even moderately large recognition vocabularies ...
This paper compares the recognition accuracy of a phoneme-based automatic speech recognition system ...
Schillo C, Fink GA, Kummert F. Grapheme based speech recognition for large vocabularies. In: Intern...
In this paper, we describe a method to enhance the readability of the textual output of a large voca...
submitted for publication Abstract. Standard ASR systems typically use phoneme as the subword units....
In this paper we present a study of automatic speech recognition systems using context-dependent pho...
tems are based on modelling acoustic sub-word units such as phonemes. Phonemisation dictionaries and...
There is growing interest in using graphemes as subword units, especially in the context of the rapi...
The state-of-the-art automatic speech recognition (ASR) systems typically use phonemes as subword un...
Large vocabulary speech recognition systems traditionally represent words in terms of smaller subwor...
In today's society, speech recognition systems have reached a mass audience, especially in the field...
Standard hidden Markov model (HMM) based automatic speech recogni-tion (ASR) systems use phonemes as...
Standard hidden Markov model (HMM) based automatic speech recognition (ASR) systems use phonemes as ...
There is growing interest in using graphemes as subword units, especially in the context of the rapi...
We present a framework for discovering acoustic units and generating an associated pronunciation lex...
Automatic SpeechRecognition (ASR) systems that have even moderately large recognition vocabularies ...
This paper compares the recognition accuracy of a phoneme-based automatic speech recognition system ...
Schillo C, Fink GA, Kummert F. Grapheme based speech recognition for large vocabularies. In: Intern...
In this paper, we describe a method to enhance the readability of the textual output of a large voca...