Most Digital Signal Processors perform computations on integers, or fixed-point numbers, rather than floating-point numbers. In contrast, Digital Signal Processing algorithms are often designed with real numbers in mind and usually implemented in floating-point. Apart from finite wordlength effects that may appear during signal acquisition and intermediate computations, limits on the signal pre...

In this paper we introduce a technique to embed context-based information into an audio signal and to extract this information from the signal during playback. Context-based information can be any kind of data related to the audio signal such as the lyrics of a song or the score of a piece of music. A typical application will display the extracted information. Techniques from lossy audio compre...

Audio forensics applies the tools and techniques of audio engineering and digital signal processing to study audio data as part of a legal proceeding or an official investigation of some kind. This chapter summarizes the principal audio forensic tasks, including authentication, enhancement, and interpretation. The chapter explains the relevant procedural and historical background, presents seve...

Signal frequency estimation is a problem of significance in many applications including audio signal processing. Compressed domain audio frequency estimators that directly use the modified discrete cosine transform (MDCT) coefficients are suitable for low-complexity audio applications. A new frequency estimation approach, which can obtain the estimated value from a simple combination of three M...

TAMPERE UNIVERSITY OF TECHNOLOGY Department of Information Technology Signal Processing Laboratory VIRTANEN, TUOMAS: Audio Signal Modeling with Sinusoids Plus Noise Master of Science Thesis, 62 pages, 6 enclosure pages Examiner: Prof. Jaakko Astola, MSc Anssi Klapuri Financial support: Tampere University of Technology, Signal Processing Laboratory March 2001

A new algorithm for audio watermarking is proposed. The basic idea of the algorithm is to change the length of the intervals between salient points of the audio signal to embed data. We propose several novel ideas for practical implementations that can be used by other watermarking schemes as well. The algorithm is robust to common audio processing operations e.g. mp3 lossy compression, low pas...

Digital audio processing applications are getting popularity with the time. Audio data compression, summarization, speech recognition, speaker identification, speech and music separation, music genre classifications, singer identification, gender detection and many more are there. Feature selection is the curial part of these applications. Various audio signal features are reviewed here especia...

In the framework of audio signal analysis, there have been recent significant advances in two directions: sparse and structured representation. In fact, sparse decompositions of audio signals are shown to be effective, and appear to be extremely useful in many signal processing applications: compression, source separation, noise reduction... A second point of view tries to take advantage of the...

Music visualization is expected to play an important role in enhancing enjoyment of music. This paper surveys music visualization systems using musical audio signal processing and introduces our prototype system of a music player with a function of visualizing instrumentation.

Faustine is the first interpreter for the digital audio signal processing language Faust and its vector extension. This domainspecific language for sample-based audio is highly expressive and can be efficiently compiled. Faustine has been designed and implemented, in OCaml, to validate the Faust multirate vector extension proposed in the literature, without having to modify the sophisticated Fa...