Frame-Synchronous and Local Confidence Measures for on-the-fly Automatic Speech Recognition.

International audienceThis paper presents several new confidence measures with the major advantage that they can be evaluated as soon as possible without having to wait for the recognition process to be completed. We have defined two kinds of confidence measures. The first one can be computed synchronously with the frame processed by the engine and the second one with a slight delay. Such measures are useful for driving the recognition process by modifying the likelihood score or for validating recognised words in on-the-fly applications such as keyword spotting task and on-line automatic speech transcription for deaf people. The EER evaluation on a French broadcast news corpus shows a performance close to the batch version of these measures (23.0% against 22.0% of EER) with only 0.84s of data before and after the word to be analysed