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1
Development and Utility of Automatic Language Processing Technologies. Volume 2
In: DTIC (2014)
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2
What's Wrong With Automatic Speech Recognition (ASR) and How Can We Fix It?
In: DTIC (2013)
Abstract: Seedling effort sponsored by IARPA to investigate the sources of speech recognition errors associated with noisy or unusual acoustic conditions. Research was conducted through two separate mechanisms: an in-depth study of the source of errors in the acoustic model, using a novel sampling process to quantify the effects that the two major Hidden Markov Model (HMM) assumptions have on recognition accuracy; and a broader study of problems in speech recognition relying on a surveys of area experts and relevant literature. The in-depth study demonstrates that a lack of robustness (to mismatched training/test conditions) is a significant source of error and that the sensitivity to such mismatches in the acoustic representations is a prominent source of errors. The results also show that in the case of matched conditions, one of the incorrect assumptions inherent to the standard statistical models is the dominant source of errors. A survey of automatic speech recognition (ASR) researchers and of the ASR literature provides a further sense of the community?s perspective on the topic. The report concludes with some speculations for fruitful directions of future research. The authors also suggest some extensions of this line of inquiry to other prediction and classification problems beyond speech recognition.
Keyword: *ACOUSTICS; *MARKOV PROCESSES; *SPEECH RECOGNITION; ACCURACY; ACOUSTIC EQUIPMENT; Acoustics; ADAPTERS; ASR(AUTOMATIC SPEECH RECOGNITION); AUTOMATIC; CLASSIFICATION; ERRORS; MATHEMATICAL MODELS; MODELS; PREDICTIONS; RECOGNITION; SAMPLING; SENSITIVITY; SOURCES; SPEECH; STATISTICAL ANALYSIS; SURVEYS; TRAINING; Voice Communications
URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA590075
http://www.dtic.mil/docs/citations/ADA590075
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3
Speaker Clustering for a Mixture of Singing and Reading (Preprint)
In: DTIC (2012)
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4
Open-Source Multi-Language Audio Database for Spoken Language Processing Applications
In: DTIC (2012)
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5
Speech Processing in Realistic Battlefield Environments (Le Traitement de la Parole en Environnement de Combat Realiste)
In: DTIC (2009)
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6
Perturbation and Pitch Normalization as Enhancements to Speaker Recognition
In: DTIC (2009)
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7
Listener Detection of Talker Stress in Low-Rate Coded Speech
In: DTIC (2008)
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8
Multimodal Meeting Capture and Understanding with the CALO Meeting Assistant
In: DTIC (2007)
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9
Speaker Adaptation of Language Models for Automatic Dialog Act Segmentation of Meetings
In: DTIC (2007)
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10
Leveraging Multimodal Redundancy for Dynamic Learning, with SHACER - a Speech and HAndwriting reCognizER
In: DTIC (2007)
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11
Speaker Segmentation and Clustering Using Gender Information
In: DTIC (2006)
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12
Multilingual Phoneme Models for Rapid Speech Processing System Development
In: DTIC (2006)
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13
Human Language Technology: Opportunities and Challenges
In: DTIC (2005)
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14
Automatic Multi-Language Phonetic Transcribing System
In: DTIC AND NTIS (2002)
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15
Activity Detection for Information Access to Oral Communication
In: DTIC (2001)
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16
Clustering of Context Dependent Speech Units for Multilingual Speech Recognition
In: DTIC (2000)
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17
Speech Intelligibility of Native and Non-Native Speech
In: DTIC (2000)
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18
Speech Recognition by Goats, Wolves, Sheep and Non-Natives
In: DTIC (2000)
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19
An Overview of the EURESCOM MIVA Project
In: DTIC (2000)
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20
How Foreign are 'Foreign' Speech Sounds? Implications for Speech Recognition and Speech Synthesis
In: DTIC (2000)
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