Songs Search Using Human Humming Voice

The system is developed to find songs stored in the database using human humming voice, whereby a sample of the humming voice is compared to songs stored in the system. The main function of the system is to find songs only by humming to the melody of the song. The scopes for this project are human humming voice, voice capture in WA V format, songs database, and MIDI file comparing algorithm. Methodologies used in this system are based on system analysis and design methodology comprising planning, analysis, design and implementation. Java programming language is used to build the system. The system has the functionality of humming voice recording and algorithms comparing both humming voice and song files in the system to fmd the right song. The intended result of this system is to display the titles of the song and similarity percentage between humming voice melody and songs in the system

SongComposer: A Large Language Model for Lyric and Melody Composition in Song Generation

We present SongComposer, an innovative LLM designed for song composition. It could understand and generate melodies and lyrics in symbolic song representations, by leveraging the capability of LLM. Existing music-related LLM treated the music as quantized audio signals, while such implicit encoding leads to inefficient encoding and poor flexibility. In contrast, we resort to symbolic song representation, the mature and efficient way humans designed for music, and enable LLM to explicitly compose songs like humans. In practice, we design a novel tuple design to format lyric and three note attributes (pitch, duration, and rest duration) in the melody, which guarantees the correct LLM understanding of musical symbols and realizes precise alignment between lyrics and melody. To impart basic music understanding to LLM, we carefully collected SongCompose-PT, a large-scale song pretraining dataset that includes lyrics, melodies, and paired lyrics-melodies in either Chinese or English. After adequate pre-training, 10K carefully crafted QA pairs are used to empower the LLM with the instruction-following capability and solve diverse tasks. With extensive experiments, SongComposer demonstrates superior performance in lyric-to-melody generation, melody-to-lyric generation, song continuation, and text-to-song creation, outperforming advanced LLMs like GPT-4.Comment: project page: https://pjlab-songcomposer.github.io/ code: https://github.com/pjlab-songcomposer/songcompose

Speech dysprosody but no music ‘dysprosody’ in Parkinson’s disease

AbstractParkinson’s disease is characterized not only by bradykinesia, rigidity, and tremor, but also by impairments of expressive and receptive linguistic prosody. The facilitating effect of music with a salient beat on patients’ gait suggests that it might have a similar effect on vocal behavior, however it is currently unknown whether singing is affected by the disease. In the present study, fifteen Parkinson patients were compared with fifteen healthy controls during the singing of familiar melodies and improvised melodic continuations. While patients’ speech could reliably be distinguished from that of healthy controls matched for age and gender, purely on the basis of aural perception, no significant differences in singing were observed, either in pitch, pitch range, pitch variability, and tempo, or in scale tone distribution, interval size or interval variability. The apparent dissociation of speech and singing in Parkinson’s disease suggests that music could be used to facilitate expressive linguistic prosody

A Lyrics-matching QBH System for Interactive Environments

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Songs Search Using Human Humming Voice

The system is developed to find songs stored in the database using human humming voice, whereby a sample of the humming voice is compared to songs stored in the system. The main function of the system is to find songs only by humming to the melody of the song. The scopes for this project are human humming voice, voice capture in WA V format, songs database, and MIDI file comparing algorithm. Methodologies used in this system are based on system analysis and design methodology comprising planning, analysis, design and implementation. Java programming language is used to build the system. The system has the functionality of humming voice recording and algorithms comparing both humming voice and song files in the system to fmd the right song. The intended result of this system is to display the titles of the song and similarity percentage between humming voice melody and songs in the system