NDLI: Cross-language acoustic model refinement for the Indonesian language

Content Provider	IEEE Xplore Digital Library
Author	Martin, T. Sridharan, S.
Copyright Year	2005
Description	Author affiliation: Speech, Audio, Image & Video Technol., Queensland Univ. of Technol., Brisbane, Qld., Australia (Martin, T.; Sridharan, S.)
Abstract	Porting ASR capabilities to many languages is hindered by a lack of transcribed acoustic data. Cross-language adaptation techniques seek to address this problem by substituting models trained in resource-rich source languages to recognise speech in resource-poor target languages. The differences in coarticulatory effects between the source and target languages, together with unwanted pronunciation and channel variation, result in recognition rates that are typically much worse then those achieved by well trained monolingual systems. We present a technique which makes more effective use of limited adaptation data by structuring the state distributions to suit the coarticulatory occurrences in the target language. Additionally, the proposed technique provides a more suitable method for synthesising unseen contexts. Evaluation of this technique is presented for a word recognition task using English and Spanish source language acoustic models trained using Switchboard and CallHome databases, respectively. Using 25 minutes of Indonesian speech for target language adaptation data, this technique achieved absolute improvements of 3.69% and 6.31% for English and Spanish sources, respectively, when compared to traditional adaptation techniques. Using 90 minutes of adaptation data, absolute improvements of 3.22% and 3.07% were achieved.
Sponsorship	IEEE Signal Processing Soc
File Size	262368
File Format	PDF
ISBN	0780388747
ISSN	15206149
DOI	10.1109/ICASSP.2005.1415251
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-03-23
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Natural languages Automatic speech recognition Speech recognition Target recognition Telephony Databases Vocabulary Australia Speech synthesis Availability
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Language adaptation of multilingual phone models for vocabulary independent speech recognition tasks

Automatic language identification using large vocabulary continuous speech recognition

Unsupervised speaker adaptation for telephone call transcription

Adaptation strategies for the acoustic and language models in bilingual speech transcription

Context-dependent units for vocabulary-independent Spanish speech recognition

Language identification through large vocabulary continuous speech recognition

Experiments in keypad-aided spelling recognition

Syllable-based acoustic-phonetic decoding and wordhypotheses generation in fluently spoken speech

Using Morphological Information for Robust Language Modeling in Czech ASR System

Cross-language acoustic model refinement for the Indonesian language

Similar Documents

Language adaptation of multilingual phone models for vocabulary independent speech recognition tasks

Automatic language identification using large vocabulary continuous speech recognition

Unsupervised speaker adaptation for telephone call transcription

Adaptation strategies for the acoustic and language models in bilingual speech transcription

Context-dependent units for vocabulary-independent Spanish speech recognition

Language identification through large vocabulary continuous speech recognition

Experiments in keypad-aided spelling recognition

Syllable-based acoustic-phonetic decoding and wordhypotheses generation in fluently spoken speech

Using Morphological Information for Robust Language Modeling in Czech ASR System

Cross-language acoustic model refinement for the Indonesian language