12580255
Comparison of Word and Subword Indexing Techniques for Mandarin Chinese Spoken Document Retrieval
In this paper, we investigate the use of words and subwords (including both characters and syllables) in audio indexing for Mandarin Chinese spoken document retrieval. Two retrieval approaches, including the well-known vector space model approach and the newly proposed HMM/Ngram-based approach, are used in the present work. We focus on the use of an entire Chinese textual story (from a newspaper) as a query to retrieve Mandarin Chinese spoken documents (from news broadcasts). Experiments are based on the Topic Detection and Tracking Corpora.
7772067
Extractive Chinese Spoken Document Summarization Using Probabilistic Ranking Models
The purpose of extractive summarization is to automatically select indicative sentences, passages, or paragraphs from an original document according to a certain target summarization ratio, and then sequence them to form a concise summary. In this paper, in contrast to conventional approaches, our objective is to deal with the extractive summarization problem under a probabilistic modeling framework. We investigate the use of the hidden Markov model (HMM) for spoken document summarization, in which each sentence of a spoken document is treated as an HMM for generating the document, and the sentences are ranked and selected according to their likelihoods. In addition, the relevance model (RM) of each sentence, estimated from a contemporary text collection, is integrated with the HMM model to improve the representation of the sentence model. The experiments were performed on Chinese broadcast news compiled in Taiwan. The proposed approach achieves noticeable performance gains over conventional summarization approaches.
11937214
A Query-by-Singing Technique for Retrieving Polyphonic Objects of Popular Music
This paper investigates the problem of retrieving popular music by singing. In contrast to the retrieval of MIDI music, which is easy to acquire the main melody by the selection of the symbolic tracks, retrieving polyphonic objects in CD or MP3 format requires to extract the main melody directly from the accompanied singing signals, which proves difficult to handle well simply using the conventional pitch estimation. To reduce the interference of background accompaniments during the main melody extraction, methods are proposed to estimate the underlying sung notes in a music recording by taking into account the characteristic structure of popular song. In addition, to accommodate users’ unprofessional or personal singing styles, methods are proposed to handle the inaccuracies of tempo, pause, transposition, or off-key, etc., inevitably existing in queries. The proposed system has been evaluated on a music database consisting of 2613 phrases extracted manually from 100 Mandarin pop songs. The experimental results indicate the feasibility of retrieving pop songs by singing.
2984995
Query-By-Example Technique for Retrieving Cover Versions of Popular Songs with Similar Melodies
Retrieving audio material based on audio queries is an important and challenging issue in the research field of content-based access to popular music. As part of this research field, we present a preliminary investigation into retrieving cover versions of songs specified by users. The technique enables users to listen to songs with an identical tune, but performed by different singers, in different languages, genres, and so on. The proposed system is built on a query-by-example framework, which takes a fragment of the song submitted by the user as input, and returns songs similar to the query in terms of the main melody as output. To handle the likely discrepancies, e.g., tempos, transpositions, and accompaniments between cover versions and the original song, methods are presented to remove the non-vocal portions of the song, extract the sung notes from the accompanied vocals, and compare the similarities between the sung note sequences.
15210668
A Music Retrieval System Based on Query-by-Singing for Karaoke Jukebox
This paper investigates the problem of retrieving Karaoke music by singing. The Karaoke music encompasses two audio channels in each track: one is a mix of vocal and background accompaniment, and the other is composed of accompaniment only. The accompaniments in the two channels often resemble each other, but are not identical. This characteristic is exploited to infer the vocal’s background music from the accompaniment-only channel, so that the main melody underlying the vocal signals can be extracted more effectively. To enable an efficient and accurate search for a large music database, we propose a phrase onset detection method based on Bayesian Information Criterion (BIC) for predicting the most likely beginning of a sung query, and adopt a multiple-level multiple-pass Dynamic Time Warping (DTW) for melody similarity comparison. The experiments conducted on a Karaoke database consisting of 1,071 popular songs show the promising results of query-by-singing retrieval for Karaoke music.
34060618
A Minimum Boundary Error Framework for Automatic Phonetic Segmentation
This paper presents a novel framework for HMM-based automatic phonetic segmentation that improves the accuracy of placing phone boundaries. In the framework, both training and segmentation approaches are proposed according to the minimum boundary error (MBE) criterion, which tries to minimize the expected boundary errors over a set of possible phonetic alignments. This framework is inspired by the recently proposed minimum phone error (MPE) training approach and the minimum Bayes risk decoding algorithm for automatic speech recognition. To evaluate the proposed MBE framework, we conduct automatic phonetic segmentation experiments on the TIMIT acoustic-phonetic continuous speech corpus. MBE segmentation with MBE-trained models can identify 80.53% of human-labeled phone boundaries within a tolerance of 10 ms, compared to 71.10% identified by conventional ML segmentation with ML-trained models. Moreover, by using the MBE framework, only 7.15% of automatically labeled phone boundaries have errors larger than 20 ms.
5230665
Finding global icebergs over distributed data sets
Finding icebergs–items whose frequency of occurrence is above a certain threshold–is an important problem with a wide range of applications. Most of the existing work focuses on iceberg queries at a single node. However, in many real-life applications, data sets are distributed across a large number of nodes. Two naïve approaches might be considered. In the first, each node ships its entire data set to a central server, and the central server uses single-node algorithms to find icebergs. But it may incur prohibitive communication overhead. In the second, each node submits local icebergs, and the central server combines local icebergs to find global icebergs. But it may fail because in many important applications, globally frequent items may not be frequent at any node. In this work, we propose two novel schemes that provide accurate and efficient solutions to this problem: a sampling-based scheme and a counting-sketch-based scheme. In particular, the latter scheme incurs a communication cost at least an order of magnitude smaller than the naïve scheme of shipping all data, yet is able to achieve very high accuracy. Through rigorous theoretical and experimental analysis we establish the statistical properties of our proposed algorithms, including their accuracy bounds.
2672581
Debugging OWL-DL Ontologies: A Heuristic Approach
After becoming a W3C Recommendation, OWL is becoming increasingly widely accepted and used. However most people still find it difficult to create and use OWL ontologies. On major difficulty is “debugging” the ontologies – discovering why a reasoners has inferred that a class is “unsatisfiable” (inconsistent). Even for people who do understand OWL and the logical meaning of the underlining description logic, discovering why concepts are unsatisfiable can be difficult. Most modern tableaux reasoners do not provide any explanation as to why the classes are unsatisfiable. This paper presents a ‘black boxed' heuristic approach based on identifying common errors and inferences.
1927942
Tracking and segmenting people with occlusions by a sample consensus based method
One of the most difficult issues in visual tracking is to track people in groups, especially under occlusions. In this paper, we present a novel sample consensus based method, which utilizes both color and spatial information of human bodies, to model the appearance of people. We use this appearance model to segment and track people through occlusions. We show experimental results in several video sequences to validate the effectiveness of the proposed method.
34944417
Logic of Many-Sorted Theories
Certain axiomatic systems involve more than one category of fundamental objects; for example, points, lines, and planes in geometry; individuals, classes of individuals, etc. in the theory of types or in predicate calculi of orders higher than one. It is natural to use variables of different kinds with their ranges respectively restricted to different categories of objects, and to assume as substructure the usual quantification theory (the restricted predicate calculus) for each of the various kinds of variables together with the usual theory of truth functions for the formulas of the system. An axiomatic theory set up in this manner will be called many-sorted. We shall refer to the theory of truth functions and quantifiers in it as its (many-sorted) elementary logic, and call the primitive symbols and axioms (including axiom schemata) the proper primitive symbols and proper axioms of the system. Our purpose in this paper is to investigate the many-sorted systems and their elementary logics. Among the proper primitive symbols of a many-sorted system T n ( n = 2, …, ω ) there may be included symbols of some or all of the following kinds: (1) predicates denoting the properties and relations treated in the system; (2) functors denoting the functions treated in the system; (3) constant names for certain objects of the system. We may either take as primitive or define a predicate denoting the identity relation in T n .
28149553
Fingerprint Indexing Based On Symmetrical Measurement
Due to the small number of classes and uneven distribution, the Henry's fingerprint classification approach is not able to provide an efficient way to narrow down the search when identifying a person in a large database. In this paper, three symmetrical filters are used to measure different orientation structures. We proposed a new fingerprint indexing approach based on these three symmetrical measurements. Experiments conducted on the NIST database 4 show the effectiveness of the proposed approach