Data collection efforts within iTalk2Learn could be completed yielding more than 80 hours of transcribed audio-corpora for English (37h) and German (44h). These data-sets were divided into separate training and evaluation sets. Both sets need to be disjoint in order to evaluate performance in a fair manner and created in a continuous way (so as…
Precision and Recall In a previous blog-post, we discussed the use of the so-called word-error-rate (WER) in evaluating the performance of automatic speech recognition (ASR) systems. WER is a common measure for such evaluations and provides an adequate measure for applications such as sub-titling, where the correct transcription of every word is of importance. However,…
iTalk2Learn partners, Sail, explain how they evaluate automatic speech recognition systems Word Error Rate The standard measurement to assess the performance of an automatic speech recognition (ASR) system is the so-called word-error-rate (WER, (Jelinek, 1997)). WER is a minimum edit-distance measure produced by applying a dynamic alignment between the output of the ASR system and…
Conventional speech recognition systems are failing As previous research has shown, there are many differences between the speech of an adult and that of a child – both acoustically and linguistically. That is why conventional speech recognition systems modelled on adult data are failing to perform satisfactorily on children’s speech input. Speaking isn’t straightforward Human…