Abstract
It is demonstrated that clustering can be a powerful tool for selecting reference templates for speaker-independent word recognition. We describe a set of clustering techniques specifically designed for this purpose. These interactive procedures identify coarse structure, fine structure, overlap of, and outliers from clusters. The techniques have been applied to a large speech data base consisting of four repetitions of a 39 word vocabulary (the letters of the alphabet, the digits, and three auxiliary commands) spoken by 50 male and 50 female speakers. The results of the cluster analysis show that the data are highly structured containing large prominent clusters. Some statistics of the analysis and their significance are presented.
Keywords
Computer scienceCluster analysisVocabularyWord (group theory)Natural language processingArtificial intelligenceSpeech recognitionSet (abstract data type)OutlierPattern recognition (psychology)MathematicsLinguistics
Affiliated Institutions
Related Publications
A review of large-vocabulary continuous-speech
Considerable progress has been made in speech-recognition technology over the last few years and nowhere has this progress been more evident than in the area of large-vocabulary...
An exploration of large vocabulary tools for small vocabulary phonetic recognition
While research in large vocabulary continuous speech recognition (LVCSR) has sparked the development of many state of the art research ideas, research in this domain suffers fro...
Fundamentals of speech recognition
1. Fundamentals of Speech Recognition. 2. The Speech Signal: Production, Perception, and Acoustic-Phonetic Characterization. 3. Signal Processing and Analysis Methods for Speech...
Morphology-based and sub-word language modeling for Turkish speech recognition
We explore morphology-based and sub-word language modeling approaches proposed for morphologically rich languages, and evaluate and contrast them for Turkish broadcast news tran...
Publication Info
- Year
- 1979
- Type
- article
- Volume
- 27
- Issue
- 2
- Pages
- 134-141
- Citations
- 76
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
76
OpenAlex
Cite This
S. Levinson,
L. R. Rabiner,
A. E. Rosenberg
et al.
(1979).
Interactive clustering techniques for selecting speaker-independent reference templates for isolated word recognition.
IEEE Transactions on Acoustics Speech and Signal Processing
, 27
(2)
, 134-141.
https://doi.org/10.1109/tassp.1979.1163222
Identifiers
- DOI
- 10.1109/tassp.1979.1163222