Pronunciation-based ASR for names
نویسندگان
چکیده
To improve the ASR of proper names a novel method based on the generation of pronunciation variants by means of phoneme-tophoneme converters (P2Ps) is proposed. The aim is convert baseline transcriptions into variants that maximally resemble actual name pronunciations that were found in a training corpus. The method has to operate in a cross lingual setting with native Dutch persons speaking Dutch and foreign names, and foreign persons speaking Dutch names. The P2Ps are trained to act either on conventional G2Ptranscriptions or on canonical transcriptions that were provided by a human expert. Including the variants produced by the P2Ps in the lexicon of the recognizer substantially improves the recognition accuracy for natives pronouncing foreign names, but not for the other investigated combinations.
منابع مشابه
Unsupervised topic adaptation for morph-based speech recognition
Topic adaptation in automatic speech recognition (ASR) refers to the adaptation of language model and vocabulary for improved recognition of in-domain speech data. In this work we implement unsupervised topic adaptation for morph-based ASR, to improve recognition of foreign entity names. Based on first-pass ASR hypothesis similar texts are selected from a collection of articles, which are used ...
متن کاملGeneration and Pruning of Pronunciation Variants to Improve ASR Accuracy
Speech recognition, especially name recognition, is widely used in phone services such as company directory dialers, stock quote providers or location finders. It is usually challenging due to pronunciation variations. This paper proposes an efficient and robust data-driven technique which automatically learns acceptable word pronunciations and updates the pronunciation dictionary to build a be...
متن کاملCAPT and its Effect on English Language Pronunciation Enhancement: Evidence from Bilinguals and Monolinguals
Nowadays there are several challenges for English teachers as well as researchers regarding how to teach foreign language pronunciation more effectively. The current study aimed to explore the effect of computer-assisted pronunciation teaching (CAPT) on Persian monolinguals and Turkmen- Persian and also Baloch- Persian bilinguals’ pronunciation considering production and perception. A sample of...
متن کاملUnsupervised Vocabulary Adaptation for Morph-based Language Models
Modeling of foreign entity names is an important unsolved problem in morpheme-based modeling that is common in morphologically rich languages. In this paper we present an unsupervised vocabulary adaptation method for morph-based speech recognition. Foreign word candidates are detected automatically from in-domain text through the use of letter n-gram perplexity. Over-segmented foreign entity na...
متن کاملWiktionary as a source for automatic pronunciation extraction
In this paper, we analyze whether dictionaries from the World Wide Web which contain phonetic notations, may support the rapid creation of pronunciation dictionaries within the speech recognition and speech synthesis system building process. As a representative dictionary, we selected Wiktionary [1] since it is at hand in multiple languages and, in addition to the definitions of the words, many...
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 2009