The IBM BOLT speech transcription system
Samuel Thomas, George Saon, Hong-Kwang Jeff Kuo, Lidia Mangu · 2015
We describe the IBM automatic speech recognition (ASR) sys-tem for the DARPA Broad Operational Language Translation (BOLT) program. The system is used to transcribe conversa-tional telephone speech (CTS) prior to machine translation for Phase 3 of the program’s Activity A. The ASR system is a com-bination of novel sequence trained ensemble deep neural net-work acoustic models on speaker adapted features and convolu-tional neural network models on two kinds of spectro-temporal representations of speech, in conjunction with a variety of class, neural network and n-gram based language models. Acoustic and language models for the recognition system are built on transcribed audio released under the program and further opti-mized for the final machine translation task as well. The evalua-tion system has a word error rate of 32.7 % on a 2 hour Egyptian Arabic development set for this task. Index Terms: Automatic speech recognition, conversational telephone speech, deep neural networks, machine translation