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Speech Recognition Software and Vidispine
Umeå University, Faculty of Science and Technology, Department of Computing Science.
2013 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

To evaluate libraries for continuous speech recognition, a test based on TED-talk videos was created. The different speech recognition libraries PocketSphinx, Dragon NaturallySpeaking and Microsoft Speech API were part of the evaluation. From the words that the libraries recognized, Word Error Rate (WER) was calculated and the results show that Microsoft SAPI performed worst with a WER of 60.8%, PocketSphinx at second place with 59.9% and Dragon NaturallySpeaking as the best with 42.6%. These results were all achieved with a Real Time Factor (RTF) of less than 1.0.

PocketSphinx was chosen as the best candidate for the intended system on the basis that it is open-source, free and would be a better match to the system. By modifying the language model and dictionary to closer resemble typical TED-talk contents, it was also possible to improve the WER for PocketSphinx to a value of 39.5%, however with the cost of RTF which passed the 1.0 limit,making it less useful for live video.

Place, publisher, year, edition, pages
2013.
Series
UMNAD, 937
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:umu:diva-71428OAI: oai:DiVA.org:umu-71428DiVA: diva2:623908
External cooperation
CodeMill
Educational program
Master of Science Programme in Computing Science and Engineering
Uppsok
Technology
Supervisors
Examiners
Available from: 2013-05-29 Created: 2013-05-29 Last updated: 2013-05-29Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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  • de-DE
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Output format
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