Our paper focuses on the gain which can be achieved on human transcription of spontaneous and prepared speech, by using the assistance of an ASR system. This experiment has shown interesting results, first about the duration of the transcription task itself: even with the combination of prepared speech + ASR, an experimented annotator needs approximately 4 hours to transcribe 1 hours of audio data. Then, using an ASR system is mostly time-saving, although this gain is much more significant on prepared speech: assisted transcriptions are up to 4 times faster than manual ones. This ratio falls to 2 with spontaneous speech, because of ASR limits for these data. Detailed results reveal interesting correlations between the transcription task and...
High quality transcription data is crucial for training automatic speech recognition (ASR) systems. ...
Real-time transcription generated by automated speech recognition (ASR) technologies with a reason...
We introduce a new method for human-machine collaborative speech transcription that is significantly...
Automatic speech recognition (ASR) in the educational environment could be a solution to address the...
This paper describes recent efforts at Linguistic Data Consortium at the University of Pennsylvania ...
This paper describes a system, based on statistical machine translation, that tries to...
As technology evolves rapidly over the years, the vast majority relies on the Internet to accomplish...
The study outlined in this paper addresses the question: Does the use of speech recognition software...
Generating accurate word-level transcripts of recorded speech for language documentation is difficul...
Managing a large-scale speech transcription task with a team of human transcribers requires effecti...
Part 2: Long and Short PapersInternational audienceReal-time transcription generated by automated sp...
International audienceAutomatic Speech Recognition systems use signal processing and machine learnin...
The analysis of spoken language has been integral to a breadth of research in social science and bey...
This paper is about Translation Dictation with ASR, that is, the use of Automatic Speech Recognitio...
We describe an efficient procedure for automatic repair of quickly transcribed (QT) speech. QT speec...
High quality transcription data is crucial for training automatic speech recognition (ASR) systems. ...
Real-time transcription generated by automated speech recognition (ASR) technologies with a reason...
We introduce a new method for human-machine collaborative speech transcription that is significantly...
Automatic speech recognition (ASR) in the educational environment could be a solution to address the...
This paper describes recent efforts at Linguistic Data Consortium at the University of Pennsylvania ...
This paper describes a system, based on statistical machine translation, that tries to...
As technology evolves rapidly over the years, the vast majority relies on the Internet to accomplish...
The study outlined in this paper addresses the question: Does the use of speech recognition software...
Generating accurate word-level transcripts of recorded speech for language documentation is difficul...
Managing a large-scale speech transcription task with a team of human transcribers requires effecti...
Part 2: Long and Short PapersInternational audienceReal-time transcription generated by automated sp...
International audienceAutomatic Speech Recognition systems use signal processing and machine learnin...
The analysis of spoken language has been integral to a breadth of research in social science and bey...
This paper is about Translation Dictation with ASR, that is, the use of Automatic Speech Recognitio...
We describe an efficient procedure for automatic repair of quickly transcribed (QT) speech. QT speec...
High quality transcription data is crucial for training automatic speech recognition (ASR) systems. ...
Real-time transcription generated by automated speech recognition (ASR) technologies with a reason...
We introduce a new method for human-machine collaborative speech transcription that is significantly...