Performance estimation of noisy speech recognition considering recognition task complexity

To ensure a satisfactory QoE (Quality of Experience) and facilitate system design in speech recognition services, it is essential to establish a method that can be used to efficiently investigate recognition performance in different noise environments. Previously, we proposed a performance estimation method using a spectral distortion measure. However, there is the problem that recognition task complexity affects the relationship between the recognition performance and the distortion value. To solve this problem, this paper proposes a novel performance estimation method considering the recognition task complexity. We confirmed that the proposed method gives accurate estimates of the recognition performance for various recognition tasks by an experiment using noisy speech data recorded in a real room.

• Type: Journal
• Year: 2010
• Where: INTERSPEECH
• Authors: Takeshi Yamada, Tomohiro Nakajima, Nobuhiko Kitawaki, Shoji Makino
• Keywords: INTERSPEECH 2010, Performance Estimation Method, Recognition Performance, Recognition Tasks, Signal Processing