Analysis of the Transitional Acoustic Features of Unaspirated Plosivess in Wuming Mandarin Based on Linear Regression Model
Abstract
References
Index Terms
- Analysis of the Transitional Acoustic Features of Unaspirated Plosivess in Wuming Mandarin Based on Linear Regression Model
Recommendations
Improving Mandarin Tone Recognition Based on DNN by Combining Acoustic and Articulatory Features Using Extended Recognition Networks
In this paper, we investigate the effectiveness of articulatory information for Mandarin tone modeling and recognition in a deep neural network --- hidden Markov model (DNN-HMM) framework. In conventional approaches, prosodic evidence (e.g., F0, ...
Acoustic model adaptation based on pronunciation variability analysis for non-native speech recognition
In this paper, pronunciation variability between native and non-native speakers is investigated, and a novel acoustic model adaptation method is proposed based on pronunciation variability analysis in order to improve the performance of a speech ...
Automatic analysis of Mandarin accented English using phonological features
The problem of accent analysis and modeling has been considered from a variety of domains, including linguistic structure, statistical analysis of speech production features, and HMM/GMM (hidden Markov model/Gaussian mixture model) model classification. ...
Comments
Information & Contributors
Information
Published In

Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Check for updates
Qualifiers
- Research-article
- Research
- Refereed limited
Conference
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 9Total Downloads
- Downloads (Last 12 months)9
- Downloads (Last 6 weeks)2
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format