J. Foote. An overview of audio information retrieval. Multimedia Systems, 7(1):2--10, 1999.  Home/Search Document Details and Download
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A Speech/Music Discriminator Based on RMS and Zero-Crossings - Panagiotakis, Tziritas (2004) (2 citations) (Correct)
....classification, search and retreival of audio signals is presented. The sound analysis uses the signal energy,pitch, central frequency, spectral bandwidth and harmonicity. This system is applied mainly in audio data collections. In a more general framework related issues are reviewed in [1]. In [3] and [6] cepstral coefficients are used for classifying or segmenting speech and music. Moreno and Rifkin [3] model these data using Gaussian mixtures and train a support vector machine for the classification. On a set of 173 hours of audio signals collected from the WWW a performance of ....
J. Foote. An overview of audio information retrieval. Multimedia Systems, pages 2--10, 1999.
Soundspotter -- A Prototype System For Content-Based.. - Christian Spevak Faculty (2002) (4 citations) (Correct)
....similarity as similarity in spectral evolution, which is measured by comparing sequences of feature vectors. The current implementation of our system is a prototype designed to evaluate different retrieval algorithms. Our research fits into the emerging discipline of audio information retrieval [1, 2]. Related work in this area includes content based retrieval and browsing of sound files in audio databases [3, 4, 5] audio classification [6, 7] and sound source recognition [8] Soundspotter is based on a modular architecture consisting of four stages. First, a frame based feature extraction ....
Jonathan Foote, "An overview of audio information retrieval, " Multimedia Systems, vol. 7, pp. 2--10, 1999.
Content-based Organization and Visualization of Music Archives - Pampalk, Rauber, Merkl (2002) (5 citations) (Correct)
....One of the first audio retrieval approaches dealing with music was presented in [33] where attributes such as the pitch, loudness, brightness and bandwidth of speech and individual musical notes were analyzed. Several overviews of systems based on the raw audio data have been presented, e.g. [9, 17]. However, most of these systems do not treat content based music retrieval in detail, but mainly focus on speech or partly speech audio data. Furthermore, only few approaches in the area of contentbased music analysis have utilized the framework of psychoacoustics. Psychoacoustics deals with the ....
J. Foote. An overview of audio information retrieval. ACM Multimedia Systems, 7(1):2 10, 1999.
Arthur: Retrieving Orchestral Music by Long-Term Structure - Foote (2000) (12 citations) (Correct)
....Lintgen) 2. PREVIOUS WORK Much work in music retrieval has concentrated on symbolic or MIDI representations, perhaps due to the difficulty of extracting useful features from audio. Despite this, a growing number of researchers are investigating music and audio retrieval in the waveform domain [3]. A particular approach to rapid audio search was done by a group at NTT [4] In this method known audio segments were detected in longer recordings by comparing histograms of the power spectrum in 7 frequency bands, and or zero crossing rate. This method was optimized for speed, and could locate ....
Foote, J., "An Overview of Audio Information Retrieval," in Multimedia Systems, 7(1), pp. 2-11, January 1999, ACM Press/Springer-Verlag.
COSC460: Music Selection for Internet Radio - Weiss (2000) (Correct)
....method, 14 proposed in [2] matches the query based on the inputted rhythm. Methods exist to extract speech from audio samples, and then provide speech to text transcription, allowing users to query based on words in the song audio sample. For an overview of audio retrieval systems refer to [3]. A system for automatic genre extraction from a music track is described in [14] while [15] presents another general work on audio classification and retrieval. Music selection, on the other hand, does not look inside the audio sample, and a track is not selected due to a specific query by a ....
Foote, J. An Overview of Audio Information Retrieval, Multimedia Systems (1999), Vol. 7, No. 1, pp. 2--10, January.
Multifeature Audio Segmentation For Browsing And Annotation - George Tzanetakis Computer (1999) (Correct)
....and acoustical features, can specify classes based on these features and can ask the engine to retrieve similar or dissimilar sounds. In this paper we focus on audio data and especially music. Recently, a number of techniques for automatic analysis of audio information have been proposed [3]. These approaches work reasonably well for restricted classes of audio and are based on pattern recognition techniques for classification. Unlike these methods, we directly segment audio into regions based on temporal changes without trying to classify the content. The remainder of this paper is ....
J. Foote, "An overview of audio information retrieval," ACM Multimedia Systems, vol. 7, pp. 2--10, 1999.
A Framework for Audio Analysis Based on Classification and.. - Tzanetakis, Cook (1999) (1 citation) (Correct)
....searching. This approach works well and has the advantage of using well known and supported techniques. On the other hand, using current interfaces human annotation of audio is extremely time consuming. Recently, a number of techniques for automatic analysis of audio information have been proposed [6]. These approaches work reasonably well for restricted classes of audio. Based on these techniques, a completely automatic annotation system for audio could be envisioned. Although not impossible in theory, there are two problems with such an approach. The first is that current systems are not ....
....retrieval techniques and fast browsing can greatly accelerate this process. 1.2 Related Work A number of techniques for audio analysis have recently been proposed. In this section, some of these systems , relevant to our work, will be briefly described. A more complete overview can be found in [6]. A robust multi feature music speech discriminator is described in [18] A similar discriminator is used in [15] to initially separate speech from music and then detect phonemes or notes accordingly. A multi feature classifier based on spectral moments for recognition of steady state instrument ....
J Foote. An overview of audio information retrieval. ACM Multimedia Systems, 7:2--10, 1999.
MARSYAS: A framework for audio analysis - Tzanetakis, Cook (2000) (14 citations) (Correct)
....searching. This approach works well and has the advantage of using well known and supported techniques. On the other hand, using current interfaces human annotation of audio is extremely time consuming. Recently, a number of techniques for automatic analysis of audio information have been proposed [Foote, 1999]. These approaches work reasonably well for restricted classes of audio. Based on these techniques, a completely automatic annotation system for audio could be envisioned. Although not impossible in theory, there are two problems with such an approach. The first is that current systems are not ....
....retrieval techniques and fast browsing can greatly accelerate this process. 1.2 Related Work A number of techniques for audio analysis have recently been proposed. In this section, some of these systems , relevant to our work, will be briefly described. A more complete overview can be found in [Foote, 1999]. A robust multi feature music speech discriminator is described in [Scheirer and Slaney, 1997] A similar discriminator is used in [Rossignol et al. 1998] to initially separate speech from music and then detect phonemes or notes accordingly. A multi feature classifier based on spectral ....
Foote, J. (1999). An overview of audio information retrieval. ACM Multimedia Systems, 7:2--10.
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J. Foote. An overview of audio information retrieval. Multimedia Systems, 7(1):2-10, 1999.
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