Sound database retrieved by sound.

Abstract

In this paper, we propose a sound-database system, which is able to extract stored data using sound as a key for the query. This ability realizes the sound extraction without having to specify the acoustical characteristics of the sound. The system repetitively searches and presents sounds, which have similarity in timbre to the key sound, until the user finds a satisfactory sample. The parameters that characterize a sound's timbre, which is a psychoacoustical factor for sound perception, are adopted as the sound's indices in the database and used for similarity matching in the searching process. Because the definition of similarity in sounds differs from user to user, the proposed system is equipped with an adaptive preference-weighted searching mechanism that adapts its searching focus based on the user's preference. Because of the ability of the proposed system to realize an intuitive query, this system can be broadly used by a user without special acoustical knowledge.

Environmental Sound Perception: Metadescription and Modeling Based on Independent Primary Studies

“…From an application point of view, the relevant acoustic features obtained for the three categories of sounds will allow us to conceive of perceptually relevant organization structures of large environmental sound collections and to propose retrieval systems using an intuitive query process by searching for sounds that are similar to a target sound in that kind of database. The search will be based on similarity metrics computed from the acoustic features, and stored with the sounds in the database as proposed by previous studies for musical sounds (Blum et al [28], Misdariis et al [29], Qi et al [30]). From a larger perspective, these results should also contribute to the elaboration of a functional Computer-Aided Sound Design framework as they will help users to describe, associate, compare, share, and finally manipulate sounds that can be considered as prototypes or initial ideas of concepts that the designer has in mind and tries to materialize in the framework of a specific project.…”

Multiobjective Time Series Matching for Audio Classification and Retrieval

“…These vectors were then compared with the Euclidean distance as similarity metric. This approach known as Bag-Of-Features (BOF) has been extended using larger sets of features [76] or adding relevance feedback [59] in which the user selects its preferred results for refinement. Subramanya et al [70] used frequency coefficients from spectral decompositions and showed the superiority of DCT.…”

“…We show how MOTS query results handle this aspect by being presented to users in an informative way. Finally, when an example is unknown or difficult to generate, the query should help the user determine what he is seeking by being specified in a way as close as possible to the underlying nature of audio properties [59]. We present two potential applications of the MOTS approach for innovative audio querying in order to cope with the multidimensionality of timbre perception.…”

Automatic Playlist Generation from Self-Organizing Music Map

“…However, due to its simplicity and intuitiveness, we utilized the Euclidean distance to measure the similarity of the songs in our system. Some multimedia retrieval systems [18,19] applied interactive and adaptive schemes to extract multimedia contents, not necessarily music, that match the users' criteria. While this idea is definitely interesting and important for building automatic playlist generation systems, we take different approach.…”