NDLI: Towards realizing gesture-to-speech conversion with a HMM-based bilingual speech synthesis system

Content Provider	IEEE Xplore Digital Library
Author	Hongwu Yang Xiaochun An Dong Pei Yitong Liu
Copyright Year	2014
Description	Author affiliation: Sch. of Inf. & Commun. Eng., Beijing Univ. of Posts & Telecommun., Beijing, China (Yitong Liu) \|\| Coll. of Phys. & Electron. Eng., Northwest Normal Univ., Lanzhou, China (Hongwu Yang; Xiaochun An; Dong Pei)
Abstract	This paper realizes a gesture-to-speech conversion system to solve the communication problem between healthy people and speech disorders. An improved speeded up robust features (SURF) algorithm is adopted for static gesture recognition by combining Kinect sensor. Meanwhile, a Hidden Markov Model (HMM) based Mandarin-Tibetan bilingual speech synthesis system is developed by using speaker adaptive training. A set of semantic rules is designed for the static gestures. Chinese or Tibetan context-dependent labels of recognized static gestures are generated according to the semantic rules. The recognized gestures are finally converted to the Mandarin or Tibetan by using the Mandarin-Tibetan bilingual speech synthesis system with the context-dependent labels. Tests show that the static gesture recognition rate of the designed system achieves 97.1%. Subjective evaluation demonstrates that synthesized speech can get 4.0 of the mean opinion score (MOS) on synthesized speech.
Starting Page	97
Ending Page	100
File Size	313947
Page Count	4
File Format	PDF
ISBN	9781479962846
DOI	10.1109/ICOT.2014.6956608
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-09-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Assistive technology Gesture recognition Context-dependent label Speech synthesis Improved SURF algorithm Kinect sensor Mandarin-Tibetan bilingual speech synthe-sis Semantics Hidden Markov models Static gesture recognition Speech recognition Speech Hidden Markov Model
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

Unsupervised prosodic phrase boundary labeling of Mandarin speech synthesis database using context-dependent HMM

Comparison of Syllable/Phone HMM Based Mandarin TTS

Context-dependent labels for an HMM-based speech synthesis system for Malay HMM-based speech synthesis system for Malay

An HMM-Based Gesture Recognition Method Trained on Few Samples

Automatic phrase boundary labeling for Mandarin TTS corpus using context-dependent HMM

Prosodic Chinese Sign Language Synthesis Driven by Speech

Prosodic modeling with rich syntactic context in HMM-based Mandarin speech synthesis

A Kinect based gesture recognition algorithm using GMM and HMM

Gesture spotting and recognition using salience detection and concatenated hidden markov models

Towards realizing gesture-to-speech conversion with a HMM-based bilingual speech synthesis system

Similar Documents

Unsupervised prosodic phrase boundary labeling of Mandarin speech synthesis database using context-dependent HMM

Comparison of Syllable/Phone HMM Based Mandarin TTS

Context-dependent labels for an HMM-based speech synthesis system for Malay HMM-based speech synthesis system for Malay

An HMM-Based Gesture Recognition Method Trained on Few Samples

Automatic phrase boundary labeling for Mandarin TTS corpus using context-dependent HMM

Prosodic Chinese Sign Language Synthesis Driven by Speech

Prosodic modeling with rich syntactic context in HMM-based Mandarin speech synthesis

A Kinect based gesture recognition algorithm using GMM and HMM

Gesture spotting and recognition using salience detection and concatenated hidden markov models

Towards realizing gesture-to-speech conversion with a HMM-based bilingual speech synthesis system