Description
Type of resource
text
Form
memorandums
Extent
1 text file
Place of creation
Stanford (Calif.)
September 1973
Language
English
Digital origin
reformatted digital
Creators/Contributors
- Author
- Thosar, Ravindra B.
Abstract/Contents
- Abstract
- This report explores the possibility of using a set of features for segmentation
- and recognition of continuous speech. The features are not necessarily
- "distinctive" or minimal, in the sense that they do not divide the phonemes
- into mutually exclusive subsets, and can have high redundancy. This concept of
- feature can thus avoid apriori binding between the phoneme categories to be
- recognized and the set of features defined in a particular system.
- An adaptive technique is used to find the probability of the presence of a
- feature. Each feature is treated independently of other features. An unknown
- utterance is thus represented by a feature graph with associated probabilities.
- It is hoped that such a representation would be valuable for a hypothesize-test
- paradigm as opposed to a one which operates on a linear symbolic input.
Subjects
- Subject
- Stanford Artificial Intelligence Laboratory
- Memo (Stanford Artificial Intelligence Laboratory)
- Artificial intelligence
- Genre
- Memorandums
Bibliographic information
- Finding Aid
-
- Memo
- AIM-213
- Location
- https://purl.stanford.edu/zs528qt8304
- SC1041
- Repository
- Stanford University. Libraries. Department of Special Collections and University Archives
Access conditions
- Use and reproduction:
- The materials are open for research use and may be used freely for non-commercial purposes with an attribution. For commercial permission requests, please contact the Stanford University Archives (universityarchives@stanford.edu).
- Copyright:
- Copyright © The Board of Trustees of the Leland Stanford Junior University. All rights reserved.