This paper proposed a two layer authorization mechanism, including traditional password system and rhythm recognition. The whole system includes two phases: preprocessing and usual operation for users. In preprocessing phase, users type password in a specific rhythm in order to record and analyse the characteristics of behaviour of users. In the second phase, how to verify a user in usual operation is described. The main recognition procedure consists of two stages: password check and rhythm recognition separately. User shall input correct password in correct rhythm. Here rhythm is a sequence of beats with various time intervals in between. The beat is in correspondent with every key down event. In the authorization procedure, system will check ID and password first. At the same time, system will record all time intervals of key down events. After recording all time intervals, system compares the characteristics of the resultant rhythm with that in user database. If the distance is under some threshold of error tolerance, user will be authorized. Otherwise, entering system will not be approved. The proposed two layer authorization method successfully enhances the security and efficiency of password system. The proposed distance calculation enables our calculation to be much cost effective than that of other rhythm recognition methods.

This paper presents the mathematical formulation and design methodology of progressive filtering (PF) for multimedia information retrieval, and discusses its application to the so-called query by singing/humming (QBSH), or more formally, melody recognition. The concept of PF and the corresponding dynamic programming-based design method are applicable to large multimedia retrieval systems for striking a balance between efficiency (in terms of response time) and effectiveness (in terms of recognition rate). The application of the proposed PF to a five-stage QBSH system is reported, and the experimental results demonstrate the feasibility of the proposed approach.

This paper describes the construction of a system called i-Ring that can generate a polyphonic ringtone based on a user's humming input. Algorithms used in the system for music transcription and chord generation include various techniques in speech and music signal processing, such as pitch tracking and dynamic programming, which are explained in the paper. Experimental results demonstrate the feasibility of i-Ring as a handy tool for computer assisted music composition for polyphonic ringtones.

Abstract This article describes the research and development of an efficient Music Information Retrieval (MIR) engine that is embedded in a karaoke software package targeted for Asian people's need of music retrieval. The MIR engine has a multi‐modal interface that allows queries by singing, humming, tapping, speaking, and writing. In particular, we discuss the design philosophy, technical barriers, and performance evaluation of such an engine, as well as its current and potential commercial applications. Feedbacks and feature requests from users, which greatly influence our future work, are also addressed.

paper presents the use of linear scaling and tree search in a content-based music retrieval system that can take a user's acoustic input (8-second clip of singing or humming) via a microphone and then retrieve the intended song from over 3000 candidate songs in the database. The system, known as Super MBox, demonstrates the feasibility of real-time content-based music retrieval with a high recognition rate. Super MBox first takes the user's acoustic input from a microphone and converts it into a pitch vector. Then a fast comparison engine using linear scaling and tree search is employed to compute the similarity scores. We have tested Super MBox and found the top-20 recognition rate is about 73% with about 1000 clips of test inputs from people with mediocre singing skills.

This paper presents an implementation of a content-based music retrieval system that can take a user's acoustic input (8-second clip of singing or humming) via a microphone and then retrieve the intended song from a database containing over 3000 candidate songs. The system, known as Super MBox, demonstrates the feasibility of real-time music retrieval with a high success rate. Super MBox first takes the user's acoustic input from a microphone and converts it into a pitch vector. Then a hierarchical filtering method (HFM) is used to first filter out 80% unlikely candidates and then compare the query input with the remaining 20% candidates in a detailed manner. The output of Super MBox is a ranked song list according to the computed similarity scores. A brief mathematical analysis of the two-step HFM is given in the paper to explain how to derive the optimum parameters of the comparison engine. The proposed HFM and its analysis framework can be directly applied to other multimedia information retrieval systems. We have tested Super MBox extensively and found the top-20 success rate is over 85%, based on a dataset of about singing/humming 2000 clips from people with mediocre singing skills. Our studies demonstrate the feasibility of using Super MBox as a prototype for music search engines over the Internet and/or query engines in digital music libraries.

This demo presents an implementation of a content-based music retrieval system that can take a user's acoustic input (8-second clip of singing or humming) via a microphone and then retrieve the intended song from a database containing 13,000 candidate songs. The system, known as Super MBox, demonstrates the feasibility of real-time music retrieval with a high recognition rate, which can be used for music search engines over the Internet and/or query engines in digital music libraries or karaoke machines.