Attribute-based word modeling
First Claim
1. An attribute-based speech recognition system comprising:
- A speech pre-processor that receives input speech and produces a sequence of acoustic observations representative of the input speech;
A database of context-dependent acoustic models that characterize a probability of a given sequence of sounds producing the sequence acoustic observations, each acoustic model including phonetic attributes and suprasegmental non-phonetic attributes;
A finite state language model that characterizes a probability of a given sequence of words being spoken; and
A one-pass decoder that compares the sequence of acoustic observations to the acoustic models and the language model, and outputs at least one word sequence representative of the input speech.
10 Assignments
0 Petitions
Accused Products
Abstract
An attribute-based speech recognition system is described. A speech pre-processor receives input speech and produces a sequence of acoustic observations representative of the input speech. A database of context-dependent acoustic models characterize a probability of a given sequence of sounds producing the sequence of acoustic observations. Each acoustic model includes phonetic attributes and suprasegmental non-phonetic attributes. A finite state language model characterizes a probability of a given sequence of words being spoken. A one-pass decoder compares the sequence of acoustic observations to the acoustic models and the language model, and outputs at least one word sequence representative of the input speech.
-
Citations
68 Claims
-
1. An attribute-based speech recognition system comprising:
-
A speech pre-processor that receives input speech and produces a sequence of acoustic observations representative of the input speech;
A database of context-dependent acoustic models that characterize a probability of a given sequence of sounds producing the sequence acoustic observations, each acoustic model including phonetic attributes and suprasegmental non-phonetic attributes;
A finite state language model that characterizes a probability of a given sequence of words being spoken; and
A one-pass decoder that compares the sequence of acoustic observations to the acoustic models and the language model, and outputs at least one word sequence representative of the input speech. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34)
-
-
35. An attribute-based method of speech recognition comprising:
-
Pre-processing input speech to produce a sequence of acoustic observations representative of the input speech;
Characterizing, with context-dependent acoustic models, a probability of a given sequence of sounds producing the sequence of acoustic observations, each acoustic model including phonetic attributes and suprasegmental non-phonetic attributes;
Characterizing, with a finite state language model, a probability of a given sequence of words being spoken; and
Comparing, with a one-pass decoder, the sequence of acoustic observations to the acoustic models and the language model, and outputs at least one word sequence representative of the input speech. - View Dependent Claims (36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68)
-
Specification