Continuous HMM and Its Enhancement for Singing/Humming Query Retrieval

The use of HMM (Hidden Markov Models) for speech recognition has been successful for various applications in the past decades. However, the use of continuous HMM (CHMM) for melody recognition via acoustic input (MRAI for short), or the so-called query by singing/humming, has seldom been reported, partly due to the difference in acoustic characteristics between speech and singing/humming inputs. This paper will derive the formula of CHMM training for frame-based MRAI. In particular, we shall propose enhancement to CHMM and demonstrate that with the enhancement scheme, CHMM can compare favourably with DTW in both efficiency and effectiveness.

• Type: Conference
• Year: 2005
• Where: ISMIR
• Authors: Jyh-Shing Roger Jang, Chao-Ling Hsu, Hong-Ru Lee
• Keywords: CHMM, Continuous Hmm, Hidden Markov Models, Information Retrieval, ISMIR 2005