Hsuan-Huei Shih

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A fast H.264 Intra prediction mode selection scheme is proposed in this work. The objective is to reduce the encoder complexity without significant rate-distortion performance degradation. The proposed method uses spatial and transform domain features of the target block jointly to filter out the majority of candidate modes. This is justified by examining(More)
A fast mode decision method for intra prediction in H.264 is proposed in this work to reduce the encoder complexity. The proposed algorithm adopts a multistage sequential mode decision process that uses joint spatial and transform domain features to filter out unlikely candidate modes and. in the final stage, a simplified rate-distortion optimization method(More)
A new phone level hidden Markov model approach applied to human humming transcription is proposed in this research. A music note has two important attributes, i.e. pitch and duration. The proposed system generates multidimensional humming transcriptions , which contain both pitch and duration information. Query by humming provides a natural means for(More)
A new statistical pattern recognition approach applied to human humming transcription is proposed in this research. A music note has two important attributes, i.e. pitch and duration. The proposed algorithm generates multidimensional humming transcriptions , which contain both pitch and duration information. Query by humming provides a natural means for(More)
Extraction of repetitive patterns of the main melody in a given music piece is investigated in this research. A dictionary-based approach is proposed to achieve the task. The input to the proposed system is a piece of music consisting of numerical music scores (e.g. the MIDI file format), and other music forms such as the sound wave have to be converted to(More)
Advances in music retrieval research greatly depend on appropriate database resources and their meaningful organization. In this paper we describe the data collection efforts related to the design of query by humming (QBH) systems. We also provide a statistical analysis for categorizing the collected data, especially focusing on inter-subject variability(More)
A statistical pattern recognition approach applied to human humming data is examined in this research. Query by humming provides a natural means for content-based retrieval from music databases. The proposed system aims at providing a robust front-end for such an application. The segment of a note in the humming waveform is modeled by a hidden Markov model(More)
Automatic melody extraction techniques can be used to index and retrieve songs in music databases. Here, we consider a piece of music consisting of numerical music scores (e.g. the MIDI file format) as the input. Segmentation is done based on the tempo information, and a music score is decomposed into bars. Each bar is indexed, and a bar index table is(More)