This paper proposes a symbolic pattern retrieval method using emotional feature vectors. Queries and symbolic patterns are represented by emotional vectors composed of eight numerical parameters. Since the proposed method uses numerical vectors close to raw data instead of recognized text, the information loss by data conversion is small. This point is advantageous compared with conventional text-based search such as recent spoken document retrieval approach. Five similarity measures were compared on a test collection. The cos similarity and the Euclidean distance showed the best performance among five similarity measures. OOV analysis clarified several problems for achieving voice-input symbolic pattern retrieval.
Bibliographic reference. Suzuki, Yukiko / Aikawa, Kiyoaki (2011): "Towards voice-input symbolic pattern retrieval using parameter-based search", In INTERSPEECH-2011, 1121-1124.