Automatic Phonetic Baseform Determination
نویسندگان
چکیده
Phonetic baseforms are the basic recognition units in most large vocabulary speech recognition systems. These baseforms are usually determined by hand once a vocabulary is chosen and not modified thereafter. However, many applications of speech recognition, such as dictation transcription, are hampered by a fixed vocabulary and require the user be able to add new words to the vocabulary. At least one phonetic baseform must be assigned to each new word to properly integrate the word into the recognition system. Dictionary lookup is often unsuccessful in determining a phonetic baseform because new words are often names or task-specific jargon; also, talkers tend to have idiosyncratic pronunciations for a substantial fraction of words. This paper describes a series of experiments in which the phonetic baseform is deduced automatically for new words by utilizing actual utterances of the new word in conjunction with a set of automatically derived spelling-tosound rules. We evaluated recognition performance on new words spoken by two different talkers when the phonetic baseforms were extracted via the above approach. The error rates on these new words were found to be comparable to or better than when the phonetic baseforms were derived by hand, thus validating the basic approach.
منابع مشابه
Breadth-first search for finding the optimal phonetic transcription from multiple utterances
Extending the vocabulary of a large vocabulary speech recognition system usually requires phonetic transcriptions for all words to be known. With automatic phonetic baseform determination acoustic samples of the words in question can substitute for the required expert knowledge. In this paper we follow a probabilitistic approach to this problem and present a novel breadth-first search algorithm...
متن کاملAn approach to automatic phonetic baseform generation based on Bayesian networks
To improve the performance and the usability of the speech recognition devices, It is necessary for most applications to allow users to enter new words or personalize words to the system vocabulary. Voice-tagging technique is a simple example that use speaker dependent spoken sample to generate baseform transcriptions of the spoken words. More sophisticated techniques can use both spoken sample...
متن کاملAutomatic phonetic base form generation based on maximum context tree
To improve the performance and the usability of the speech recognition devices, it is necessary for most applications to allow users to enter new words or personalize words in the system vocabulary. The voicetagging technique is a simple example of using speaker dependent spoken samples to generate baseform transcriptions of the spoken words. More sophisticated techniques can use both spoken sa...
متن کاملTraining of Lexica for Subword-Based Speech Recognisers
In this paper we present an automatic optimal baseform determination algorithm. Given a set of subword Hidden Markov Models (HMMs) and acoustic tokens of a speciic word, we apply the tree-trellis N-best search algorithm to nd the optimal baseforms (transcriptions) in the maximum likelihood sense. The proposed algorithm is used in an iterative manner, creating a series of lexica trained from the...
متن کاملAutomatic baseform generation from acoustic data
We describe two algorithms for generating pronunciation networks from acoustic data. One is based on raw phonetic recognition and the other uses the spelling of the words and the identification of their language of origin as guides. In both cases, a pruning and voting procedure distills the noisy phonetic sequences into pronunciation networks. Recognition experiments on two large, grammar-based...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1990