语音识别中强制对齐_语音识别中的强制对齐问题-HTK

在语音识别系统中,使用HTK进行强制对齐时遇到问题,当用户未按预定义的句子准确发言时,对齐出现错误。例如,用户省略了目标句子中的单词。尽管HTK在精确对齐方面表现出色,但无法检测和避免此类不匹配。目前,CMUSphinx项目正在研发解决此问题的功能,允许将文本对齐到不精确的转录。

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I have a system where a user is asked to repeat a sentence after a prompt. It uses HTK to force-align the user-spoken-sentence to the pre-defined word level label file (of the sentence) to get a time-aligned phone level file. The HMMs have been trained on a large amount of data and give very accurate time-aligned files with HVite. My problem arises when the user does not speak the exact sentence that is required to be spoken. Let me illustrate with an example:

Word level label file of the target sentence that needs to be spoken (known to the user):

THIS IS A VERY GOOD DAY.

User says (Case 1): THIS IS A VERY GOOD DAY.

In this case, the user has repeated the exact same sentence. The time aligned file is very accurate and all is well.

User says (Case 2): THIS IS A GOOD DAY.

In this case, the forced alignment is carried out with the word level label file as given above. The resulting time-aligned file shows time instants for words that were never spoken by the user (such as VERY which exists in the original sentence but not here).

Is there a way within HTK to detect and possibly avoid this?

One solution would be some sort of a front-end pre-processor that would do speech-recognition (itself a very hard problem because it would have to have infinite vocab) and let the user know that what they have spoken is incorrect.

Are there any tools/command line options within HTK that allow me to do this?

P.S: Please let me know in case more details are needed.

Thanks,

Sriram

解决方案

The task of alignment of the text to possibly incorrect transcription is rather complex and require specialized tools. HTK forced alignment is too simplistic for that. Instead of using HVite with -a you need to build a proper wdnet which will account for possible insertions, deletion and substitutions due to the transcription mismatch.

At CMUSphinx we are currently running a project to implement this functionality. You can already use it to align text to the imprecise transcription. You can check it's progress here:

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