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Patent US5682501A successfully refreshed from Google Patents.
US5682501A
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Speech synthesis system
Assignee: International Business Machines Corp
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Filing: 1995-02-21
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Granted: 1997-10-28
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Expires: 2015-02-21
Abstract
Abstract A speech synthesis unit comprises a text processor which breaks down text into phonemes, a prosodic processor which assigns properties such as length and pitch to the phonemes based on context, and a synthesis unit which outputs an audio signal representing the sequence of phonemes according to the specified properties. The prosodic processor includes a Hidden Markov Model (HMM) to predict the durations of the phonemes. Each state of the HMM represents a duration, and the outputs are phonemes. The HMM is trained on a set of data consisting of phonemes of known identity and duration, to allow the state transition and output distributions to be calculated. The HMM can then be used for any given input sequence of phonemes to predict a most likely sequence of corresponding durations.
Inventors
- 👤 Richard Anthony Sharman
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-01 12:15
CPC Classifications
G; G10; G10L; G10L13/00; G10L13/08; G10L13/02; G10L13/04
Claims Analysis
Total Claims: 12
Claim 1
Independent Claim
98 words
A method for generating synthesized speech from input text, the method comprising the steps of: decomposing the input text into a sequence of speech units; estimating a duration value for each speech unit in the sequence of speech units; synthesizing speech based on said sequence of speech units and duration values; characterized in that said estimating step utilizes a Hidden Markov Model (HMM) to determine the most likely sequence of duration values given said sequence of speech units, wherein each state of the HMM represents a duration value and each output from the HMM is a speech unit.
Claim 2
Independent Claim
98 words
A method for generating synthesized speech from input text, the method comprising the steps of: decomposing the input text into a sequence of speech units; estimating a duration value for each speech unit in the sequence of speech units; synthesizing speech based on said sequence of speech units and duration values; characterized in that said estimating step utilizes a Hidden Markov Model (HMM) to determine the most likely sequence of duration values given said sequence of speech units, wherein each state of the HMM represents a duration value and each output from the HMM is a speech unit.
Claim 3
Dependent Claim
26 words
The method according to claim 1, wherein a state transition probability distribution of the HMM is dependent on one or more of the immediately preceding states.
Claim 4
Dependent Claim
26 words
The method according to claim 2, wherein the state transition probability distribution of the HMM is dependent on the identity of the two immediately preceding states.
Claim 5
Dependent Claim
23 words
The method according to claim 1, wherein an output probability distribution of the HMM is dependent on the current state of the HMM.
Claim 6
Dependent Claim
56 words
The method according to claim 1, further comprising the steps of: obtaining a set of speech data which has been decomposed into a sequence of speech units, each of which has been assigned a duration value; estimating a state transition probability distribution and an output probability distribution of the HMM from said set of speech data.
Claim 7
Dependent Claim
37 words
The method according to claim 5, wherein the step of estimating the state transition and output probability distributions of the HMM includes the step of smoothing the set of speech data to reduce any statistical fluctuations therein.
Claim 8
Dependent Claim
21 words
The method according to claim 6, wherein the set of speech data is obtained by means of a speech recognition system.
Claim 9
Dependent Claim
23 words
The method according to claim 7, wherein the determination of the most likely sequence of duration values is performed using the Viterbi algorithm.
Claim 10
Dependent Claim
15 words
The method according to claim 8, wherein each of said speech units is a phoneme.
Claim 11
Dependent Claim
108 words
A speech synthesis system for generating synthesized speech from input text comprising: a text processor for decomposing the input text into a sequence of speech units; a prosodic processor for estimating a duration value for each speech unit in the sequence of speech units; a synthesis unit for synthesizing speech based on said sequence of speech units and duration values; and characterized in that said prosodic processor utilizes a Hidden Markov Model (HMM) to determine the most likely sequence of duration values given said sequence of speech units, wherein each state of the HMM represents a duration value and each output from the HMM is a speech unit.
Claim 12
Dependent Claim
108 words
A speech synthesis system for generating synthesized speech from input text comprising: a text processor for decomposing the input text into a sequence of speech units; a prosodic processor for estimating a duration value for each speech unit in the sequence of speech units; a synthesis unit for synthesizing speech based on said sequence of speech units and duration values; and characterized in that said prosodic processor utilizes a Hidden Markov Model (HMM) to determine the most likely sequence of duration values given said sequence of speech units, wherein each state of the HMM represents a duration value and each output from the HMM is a speech unit.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2000-10-27 | 2001-04-28 | 2001-10-28 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2004-10-27 | 2005-04-28 | 2005-10-28 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2008-10-27 | 2009-04-28 | 2009-10-28 | $7700.00 | Window Closed / Lapsed |