WFST-Based Grapheme-to-Phoneme Conversion: Open Source tools for Alignment, Model-Building and Decoding
نویسندگان
چکیده
This paper introduces a new open source, WFST-based toolkit for Grapheme-toPhoneme conversion. The toolkit is efficient, accurate and currently supports a range of features including EM sequence alignment and several decoding techniques novel in the context of G2P. Experimental results show that a combination RNNLM system outperforms all previous reported results on several standard G2P test sets. Preliminary experiments applying Lattice Minimum Bayes-Risk decoding to G2P conversion are also provided. The toolkit is implemented using OpenFst.
منابع مشابه
Improving WFST-based G2P Conversion with Alignment Constraints and RNNLM N-best Rescoring
This work introduces a modified WFST-based multiple to multiple EM-driven alignment algorithm for Grapheme-to-Phoneme (G2P) conversion, and preliminary experimental results applying a Recurrent Neural Network Language Model (RNNLM) as an Nbest rescoring mechanism for G2P conversion. The alignment algorithm leverages the WFST framework and introduces several simple structural constraints which y...
متن کاملInitial and Evaluations of an Open Source WFST-based Phoneticizer
This paper introduces a new open-source, WFST-based Grapheme-to-Phoneme system, named Phonetisaurus. The system is modular and includes support for several third-party components. The system has been implemented primarily in python, but also leverages the OpenFST framework and is intended to support both practical work as well as educational goals. Standard G2P test sets were used to evaluate t...
متن کاملEvaluations of an Open Source WFST-based Phoneticizer
This paper describes in detail some recent experiments for an Open-Source, WFST-based Grapheme-to-Phoneme system, Phonetisaurus. The system comprises several loosely coupled components and includes implementations of several G2P alignment algorithms, and simple 3-gram LMs, as well as support for several third-party components. Standard G2P evaluations were also performed on widely available tes...
متن کاملComparison of Grapheme-to-Phoneme Conversion Methods on a Myanmar Pronunciation Dictionary
Grapheme-to-Phoneme (G2P) conversion is the task of predicting the pronunciation of a word given its graphemic or written form. It is a highly important part of both automatic speech recognition (ASR) and text-to-speech (TTS) systems. In this paper, we evaluate seven G2P conversion approaches: Adaptive Regularization of Weight Vectors (AROW) based structured learning (S-AROW), Conditional Rando...
متن کاملHidden Conditional Random Fields with M-to-N Alignments for Grapheme-to-Phoneme Conversion
Conditional Random Fields have been successfully applied to a number of NLP tasks like concept tagging, named entity tagging, or grapheme-to-phoneme conversion. When no alignment between source and target side is provided with the training data, it is challenging to build a CRF system with state-of-the-art performance. In this work, we present an approach incorporating an Mto-N alignment as a h...
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 2012