AROOOGA: An Audio Search Engine for theWorldWideWeb

apotheca.hpl.hp.com

We have developed a speech recognition based audio search engine for indexing spoken documents found on the World Wide Web. Our site (http://www.compaq.com/speechbot) indexes around 20 news and talk radio shows covering a wide range of topics, speaking styles and acoustic conditions from a selection of public Web sites with multimedia archives. In this paper, we describe our system and its performance, focusing on the speech recognition and retrieval aspects. We describe our training procedure in some detail and report our historical error rate since the site launch. We also investigate the impact of Out Of Vocabulary (OOV) words. Finally we report the results of retrieval experiments which demonstrate that our system can index effectively.

2004

Sound files on the World Wide Web are accessed from web pages. To date, this relationship has not been explored extensively in the MIR literature. This paper details a series of experiments designed to measure the similarity between the public text visible on a web page and the linked sound files, the name of which is normally unseen by the user. A collection of web pages was retrieved from the web using a specially-constructed crawler. Sound file information and associated text were parsed from the pages and analyzed for similarity using common IR techniques such as TFIDF cosine measures. The results are intended to be used in the improvement of a web crawler for audio and music, as well as for MIR purposes in general.

Journal of the American Society for Information Science and Technology, 2004

Until recently, most research on music information retrieval concentrated on monophonic music. Online Music Retrieval and Searching (OMRAS) is a threeyear project funded under the auspices of the JISC (Joint Information Systems Committee)/NSF (National Science Foundation) International Digital Library Initiative which began in 1999 and whose remit was to investigate the issues surrounding polyphonic music information retrieval. Here we outline the work OMRAS has achieved in pattern matching, document retrieval, and audio transcription, as well as some prototype work in how to implement these techniques into library systems.

Signals and Communication Technology, 2017

2009

This paper describes a research work on peer-to-peer music search based on the combination of content based descriptors and textual metadata. The envisaged scenario is the one of a user who searches for documents according either to their melodic and rhythmic content, and to additional information about the title, the instrumentation, or tempo in the form of textual metadata. Two different overlay networks are used to deal with music content and text. A user interface has been developed, which allows the user to perform a query, to merge the results using alternative approaches, and to listen to the retrieved music documents.

2009

We investigate an approach to a music search engine that indexes music pieces based on related Web documents. This allows for searching for relevant music pieces by issuing descriptive textual queries. In this paper, we examine the effects of incorporating audio-based similarity into the text-based ranking process-either by directly modifying the retrieval process or by performing post-hoc audiobased re-ranking of the search results. The aim of this combination is to improve ranking quality by including relevant tracks that are left out by text-based retrieval approaches. Our evaluations show overall improvements but also expose limitations of these unsupervised approaches to combining sources. Evaluations are carried out on two collections, one large real-world collection containing about 35,000 tracks and on the CAL500 set.

With continued growth of music content available on the Internet, music information retrieval has attracted increasing attention. An important challenge for music searching is its ability to support both keyword and content based queries efficiently and with high precision. In this paper, we present a music query system − QueST to support both keyword and content based retrieval in large music databases. QueST stands for Query by acouStic and T extual features. The QueST approach has two distinct features. First, it provides new index schemes that can efficiently handle various queries within a uniform architecture. Concretely, we propose a hybrid structure consisting of Inverted file and Signature file to support keyword search. For content based query, we introduce the notion of similarity to capture various music semantics like melody and genre. We extract acoustic features from a music object, and map it into multiple high-dimension spaces with respect to the similarity notion using PCA and RBF neural network. Second, we design a result fusion scheme, called the Quick Threshold Algorithm, to speed up the processing of complex queries involving both textual and multiple acoustic features. Our experimental results show that QueST offers higher accuracy and efficiency compared to existing algorithms.

2nd CompMusic Workshop, 2012

In the context of the CompMusic project we are developing methods to automatically describe/annotate audio music recordings pertaining to various music cultures. As a way to demonstrate the usefulness of the methods we are also developing a system to browse and interact with specific audio collections. The system is an online web application that interfaces with all the data gathered (audio, scores plus contextual information) and all the descriptions that are automatically generated with the developed methods. In this paper we present the basic architecture of the proposed system, the types of data sources that it includes, and we mention some of the culture specific issues that we are working on for its development. The system is in a preliminary stage but it shows the potential that MIR technologies can have in browsing and interacting with music collections of various cultures.

Dagstuhl Seminar Proceedings, 2006

Abstract. Search and retrieval of specific musical content such as emotive or sonic features has become an important aspect of Music Information Retrieval system development, but only little research is user-oriented. We summarize results of an elaborate user-study that explores ...