Pronunciation network

• US 20040128132A1
• Filed: 12/30/2002
• Published: 07/01/2004
• Est. Priority Date: 12/30/2002
• Status: Abandoned Application

• Current Assignee: Intel Corporation
• Original Assignee: Intel Corporation
• Inventors: Griniasty, Meir
• Application Number:
  US10/330,537
• Publication Number:
  US 20040128132A1
• Time in Patent Office: Days
• US Class Current: 704/254
• CPC Class Codes: G10L 13/08 Text analysis or generation of parameters for speech synthesis out of text, e.g. grapheme to phoneme translation, prosody generation or stress or intonation determination
• CPC Class Codes: G10L 15/142 Hidden Markov Models [HMMs]
• CPC Class Codes: G10L 15/187 Phonemic context, e.g. pronunciation rules, phonotactical constraints or phoneme n-grams

Abstract

Briefly, a method and apparatus to generate a pronunciation network of a written word is provided. The generation of the pronunciation network may be done by receiving at least one pronunciation string of the written word from a phoneme string generator able to generate the pronunciation network of the written word. The pronunciation network may include a node list of phonemes combined from different pronunciation strings of the written word. A speech recognition apparatus based on the pronunciation network is also provided.

Claims

1. A method comprising:

generating a pronunciation network of a written word by combining two or more pronunciation strings that are selected from pronunciation strings of the written word to a list of phoneme nodes.

2. The method of claim 1, wherein generating comprises:

generating a phoneme node of the list phoneme nodes wherein, the phoneme node comprises a first tag to reference the phoneme node, a phoneme of the written word and a second tag of a precedent phoneme node of the pronunciation network.

3. The method of claim 2, wherein generating the phoneme node list comprises:

numbering in descending order the nodes of the pronunciation network and

providing a reference number to at least one of the first and second tags.

4. The method of claim 3, further comprising:

searching in ascending order the pronunciation network for a pronunciation path; and

adding the second tag to the node of the phoneme node list.

5. The method of claim 1 wherein generating comprises:

generating the pronunciation network based on the pronunciation string of the written word received from a grapheme-to-phoneme parser.

6. The method of claim 1, wherein generating comprises:

generating the pronunciation network based on the pronunciation string of the written word received from a phonetic lexicon.

7. The method of claim 1, wherein generating comprises:

generating the pronunciation network based on the pronunciation string of the written word generated from a speech.

8. The method of claim 1, further comprising:

recognizing speech based on the pronunciation network.

9. An apparatus comprising:

a phoneme string generator to generate a pronunciation string of a written word; and

a pronunciation network generator to generate a pronunciation network by combining two or more pronunciation strings of the written word to a phonemes node list.

10. The apparatus of claim 9, further comprising a memory to store the pronunciation network.

11. The apparatus of claim 9 further comprising a phonetic lexicon to provide pronunciation strings of the written word to the pronunciation network generator.

12. An apparatus comprising:

a dynamic microphone to receive a tested speech;

a speech classifier comprising at least two or more pronunciation networks to calculate a score to a tested speech and to compare the score based on the two or more pronunciation networks; and

a decision unit to recognize the tested speech based on the score.

13. The apparatus of claim 12, wherein a pronunciation network of the two or more pronunciation networks comprises a phoneme node list of a word.

14. The apparatus of claim 13, wherein a node of said phoneme node list comprises a stochastic model corresponding to a phoneme of the node.

15. The apparatus of claim 14, wherein said stochastic model is a hidden Markov model and the pronunciation network is a hidden Markov model network.

16. The apparatus of claim 15, wherein the hidden Markov model network is able to generate the node list by attaching to the node of the phoneme node list a hidden Markov model corresponding to a phoneme of the node, a local score number corresponding to a measure of likelihood of an incoming speech frame of the tested speech to the hidden Markov model and a global score number corresponding to a measure of likelihood of a pronunciation string of the tested speech.

17. The apparatus of claim 12, wherein the two or more pronunciation networks are pronunciation networks of different words.

18. The apparatus of claim 16, wherein the decision unit recognizes the tested speech based on the global score provided by hidden Markov model networks.

19. An article comprising:

a storage medium, having stored thereon instructions that, when executed, result in;

generating a pronunciation network of a written word by combining two or more pronunciation strings that are selected from pronunciation strings of the written word to a list of phoneme nodes.

20. The article of claim 19, wherein the instruction of generating, when executed, results in:

generating a phoneme node of the list phoneme nodes wherein, the phoneme node comprises a first tag to reference the phoneme node, a phoneme of the written word and a second tag of a precedent phoneme node of the pronunciation network.

21. The article of claim 20, wherein the instruction of generating the phoneme node list, when executed, results in:

numbering in descending order the nodes of the pronunciation network and

providing a reference number to the tag of the node.

22. The article of claim 21, wherein the instructions when executed, further result in:

searching ascending the pronunciation network for a pronunciation path; and

adding to the second tag to the node of the phoneme node list.

23. The article of claim 19, wherein the instruction that when executed, results in:

generating the pronunciation network based on the pronunciation string of the written word received from a grapheme to a phoneme parser.

24. The article of claim 19, wherein the instruction that when executed, results in:

generating the pronunciation network based on the pronunciation string of the written word received from a phonetic lexicon.

25. The article of claim 19, wherein the instruction that when executed, results in:

generating the pronunciation network based on the pronunciation string of the written word generated from a speech.

26. The article of claim 19, wherein the instruction that when executed, results in:

recognizing speech based on the pronunciation network.