Speech recognition performance on a new voicemail transcription task

Recent improvements in speech recognition performance on large vocabulary conversational speech (voicemail and switchboard)

In this paper we report recent improvements in word error performance on a voicemail transcription task. Last year, the speaker independent word error rate (WER) on the dev test set of the Voicemail Transcription task was reported at 35.45% [1]. This year, we report a relative 20% gain over this number. The improvements were obtained using several new algorithms and an increased amount of train...

Transcription of New Speaking Styles - Voicemail

In this paper we describe a new testbed for developing speech recognition algorithms a VoiceMail transcription task, analogous to other tasks such as the Switchboard, CallHome [1] and the Hub 4 tasks [2] which are currently used by speech recognition researchers. Spontaneous speech occurring in day-today life can broadly be classi ed into two categories (i) where the speaker does not receive an...

Automatic speech recognition performance on a voicemail transcription task

In this paper, we report on the performance of automatic speech recognition (ASR) systems on voicemail transcription. Voicemail is spontaneous telephone speech recorded over a variety of channels; consequently, it is representative of many challenging problems in speech recognition. In the course of working on this task, several algorithms were developed that focus on different components of an...

Speech recognition performance on a voicemail transcription task

A study of adaptation techniques on a voicemail transcription task

Speaker adaptation techniques have emerged as very effective and practical methods to improve ASR performance on a test speaker with only limited speech data from the speaker. We explore the use of adaptation techniques on a new Voicemail database and present some theoretical extensions of the Cluster Transformation (CT) technique. Our experiments on 40 hours of voicemail data and four clusters...