Improving Genre Classification by Combination of Audio and Symbolic Descriptors Using a Transcription Systems
نویسندگان
چکیده
Recent research in music genre classification hints at a glass ceiling being reached using timbral audio features. To overcome this, the combination of multiple different feature sets bearing diverse characteristics is needed. We propose a new approach to extend the scope of the features: We transcribe audio data into a symbolic form using a transcription system, extract symbolic descriptors from that representation and combine them with audio features. With this method, we are able to surpass the glass ceiling and to further improve music genre classification, as shown in the experiments through three reference music databases and comparison to previously published performance results.
منابع مشابه
Mirex 2007 Combining Audio and Symbolic Descriptors for Music Classification from Audio
Recent research in music genre classification hints at a glass ceiling being reached using timbral audio features. To overcome this, the combination of multiple different feature sets bearing diverse characteristics is needed. We propose a new approach to extend the scope of the features: We transcribe audio data into a symbolic form using a transcription system, extract symbolic descriptors fr...
متن کاملMirex 2007 Combining Audio and Symbolic Descriptors for Audio Music Similarity and Retrieval
At ISMIR 2007 we propose a new approach for an extended feature set for Audio Music Information Retrieval: We transcribe audio data into a symbolic form using a transcription system, extract symbolic descriptors from that representation and combine them with multiple audio features. In the ISMIR paper we show that by this method we are able to further improve music genre classification. At MIRE...
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