A system that tries to analyze polyphonic musical recordings of bowed-string instruments, extract synthesis parameters of individual instrument and then re-synthesize is proposed. In the analysis part, multiple F0s estimation and partials tracking are performed based on modified WGCDV (weighted greatest common divisor and vote) method and high-order HMM. Then, dynamic time warping algorithm is employed to align the above results with the score to improve the accuracy of the extracted parameters. In the re-synthesis part, simple additive synthesis is employed. Here, one can experiment on changing timbres, pitches and so on or adding vibrato or other effects on the same piece of music.

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The timbre of an instrument is usually represented by sinusoids plus noise. Spectral modeling synthesis (SMS) is an audio synthesis technique which can create musical timbre and give control over the frequency and amplitude. Additive synthesis and LPC synthesis are usually applied for synthesizing sinusoids and residuals, respectively. However, it takes fairly large computing power while implementing the algorithms. The purpose of this paper is to present GPU-based techniques of implementing SMS for real-time audio processing by using parallelism and programmability in graphics pipeline. The performance is compared to CPU-based implementations.

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In this paper, analysis and trans-synthesis of acoustic bowed string instrument recordings with new non-negative matrix factorization (NMF) procedure are presented. This work shows that it may require more than one template to represent a note according to time-varying behavior of timbre, especially played by bowed string instruments. The proposed method improves original NMF without the knowledge of tone models and the number of required templates in advance. Resultant NMF information is then converted into the synthesis parameters of the sinusoidal synthesis. Bach cello suites recorded by Fournier and Starker are used in the experiments. Analysis and trans-synthesis examples of the recordings are also provided. Index Terms—trans-synthesis, non-negative matrix factorization, bowed string instrument

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Recently, non-negative matrix factorization (NMF), which is applied to decompose signals in frequency domain by means of short-time Fourier transform (STFT), is widely used in audio source separation. Separation of low-pitch notes in recordings is of significant interest. According to time-frequency uncertainty principle, it may suffer from the tradeoff between time and frequency localizations for low-pitch sounds. Furthermore, because the window function applied to the signal causes frequency spreading, separation of low-pitch notes becomes more difficult. Instead of using power-of-2 FFT, we experiment on STFT sizes corresponding to the pitches of the notes in the signals. Computer simulations using synthetic signals show that the Source to Interferences Ratio (SIR) is significantly improved without sacrificing Sources to Artifacts Ratio (SAR) and Source to Distortion Ratio (SDR). In average, at least 2 to 6 dB improvement in SIR is achieved when compared to power-of-2 FFT of similar sizes.

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Gu-Qin as a venerable Chinese plucked-string instrument has its unique performance techniques and enchanting sounds. It is on the UNESCO Representative List of the Intangible Cultural Heritage of Humanity. It is one of the oldest Chinese solo instruments. The variation of Gu-Qin sound is so large that carefullydesigned controls of its computer synthesizer are necessary. We developed a parametric source-filter model for re-synthesizing expressive Gu-Qin notes. It is capable to cover as many as possible combinations of Gu-Qin’s performance techniques. In this paper, a brief discussion of Gu-Qin playing and its special tablature notation are made for understanding the relationship between its performance techniques and its sounds. This work includes a Gu-Qin’s musical notation system and a source-filter model based synthesizer. In addition, we implement an iOS app to demonstrate its low computation complexity and robustness. It is easy to perform improvisation of the sounds because of its friendly user interfaces.

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In this paper, we presented a flexible analysis/re-synthesis method for smoothly changing the properties of isolated notes in polyphonic instrumental music recordings. True Envelope Linear Predictive Coding (TELPC) method has been employed as the analysis/synthesis model in order to preserve the original timbre quality as much as possible due to its accurate spectral envelope estimation. We modified the conventional LPC analysis/synthesis processing by using pitch synchronous analysis frames to avoid the severe magnitude modulation problem. Smaller frames can thus be used to capture more local characteristics of the original signals to further improve the sound quality. In this framework, one can manipulate a sequence of isolated notes from two commercially available polyphonic instrumental music recordings and interesting re-synthesized results are achieved.

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Note separation in music signal processing becomes difficult when there are overlapping partials from co-existing notes produced by either the same or different musical instruments. In order to deal with this problem, it is necessary to involve certain invariant features of musical instrument sounds into the separation processing. For example, the timbre of a note of a musical instrument may be used as one possible invariant feature. In this paper, a timbre estimate is used to represent this feature such that it becomes a constraint when note separation is performed on a mixture signal. To demonstrate the proposed method, a timedependent recursive regularization analysis is employed. Spectral envelopes of different notes are estimated and a modified parameter update strategy is applied to the recursive regularization process. The experiment results show that the flaws due to the overlapping partial problem can be effectively reduced through the proposed approach.

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