Information retrieval (IR) in computing and information science is the process of obtaining information system resources that are relevant to an information need from a collection of those resources. Searches can be based on full-text or other content-based indexing. Information retrieval is the science of searching for information in a document, searching for documents themselves, and also searching for the metadata that describes data, and for databases of texts, images or sounds.
MPEG-7 is a multimedia content description standard. It was standardized in ISO/IEC 15938. This description will be associated with the content itself, to allow fast and efficient searching for material that is of interest to the user. MPEG-7 is formally called Multimedia Content Description Interface. Thus, it is not a standard which deals with the actual encoding of moving pictures and audio, like MPEG-1, MPEG-2 and MPEG-4. It uses XML to store metadata, and can be attached to timecode in order to tag particular events, or synchronise lyrics to a song, for example.
An image retrieval system is a computer system used for browsing, searching and retrieving images from a large database of digital images. Most traditional and common methods of image retrieval utilize some method of adding metadata such as captioning, keywords, title or descriptions to the images so that retrieval can be performed over the annotation words. Manual image annotation is time-consuming, laborious and expensive; to address this, there has been a large amount of research done on automatic image annotation. Additionally, the increase in social web applications and the semantic web have inspired the development of several web-based image annotation tools.
Information extraction (IE) is the task of automatically extracting structured information from unstructured and/or semi-structured machine-readable documents and other electronically represented sources. In most of the cases this activity concerns processing human language texts by means of natural language processing (NLP). Recent activities in multimedia document processing like automatic annotation and content extraction out of images/audio/video/documents could be seen as information extraction
Content-based image retrieval, also known as query by image content (QBIC) and content-based visual information retrieval (CBVIR), is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images in large databases. Content-based image retrieval is opposed to traditional concept-based approaches.
Automatic image annotation is the process by which a computer system automatically assigns metadata in the form of captioning or keywords to a digital image. This application of computer vision techniques is used in image retrieval systems to organize and locate images of interest from a database.
In music, transcription is the practice of notating a piece or a sound which was previously unnotated and/or unpopular as a written music, for example, a jazz improvisation or a video game soundtrack. When a musician is tasked with creating sheet music from a recording and they write down the notes that make up the piece in music notation, it is said that they created a musical transcription of that recording. Transcription may also mean rewriting a piece of music, either solo or ensemble, for another instrument or other instruments than which it was originally intended. The Beethoven Symphonies transcribed for solo piano by Franz Liszt are an example. Transcription in this sense is sometimes called arrangement, although strictly speaking transcriptions are faithful adaptations, whereas arrangements change significant aspects of the original piece.
Optical music recognition (OMR) is a field of research that investigates how to computationally read musical notation in documents. The goal of OMR is to teach the computer to read and interpret sheet music and produce a machine-readable version of the written music score. Once captured digitally, the music can be saved in commonly used file formats, e.g. MIDI and MusicXML . In the past it has, misleadingly, also been called "music optical character recognition". Due to significant differences, this term should no longer be used.
Computer audition (CA) or machine listening is the general field of study of algorithms and systems for audio interpretation by machines. Since the notion of what it means for a machine to "hear" is very broad and somewhat vague, computer audition attempts to bring together several disciplines that originally dealt with specific problems or had a concrete application in mind. The engineer Paris Smaragdis, interviewed in Technology Review, talks about these systems — "software that uses sound to locate people moving through rooms, monitor machinery for impending breakdowns, or activate traffic cameras to record accidents."
The National Centre for Text Mining (NaCTeM) is a publicly funded text mining (TM) centre. It was established to provide support, advice, and information on TM technologies and to disseminate information from the larger TM community, while also providing tailored services and tools in response to the requirements of the United Kingdom academic community.
Audio mining is a technique by which the content of an audio signal can be automatically analyzed and searched. It is most commonly used in the field of automatic speech recognition, where the analysis tries to identify any speech within the audio. The term ‘audio mining’ is sometimes used interchangeably with audio indexing, phonetic searching, phonetic indexing, speech indexing, audio analytics, speech analytics, word spotting, and information retrieval. Audio indexing, however, is mostly used to describe the pre-process of audio mining, in which the audio file is broken down into a searchable index of words.
Music informatics is a study of music processing, in particular music representations, fourier analysis of music, music synchronization, music structure analysis and chord recognition. Other music informatics research topics include computational music modeling, computational music analysis, optical music recognition, digital audio editors, online music search engines, music information retrieval and cognitive issues in music. Because music informatics is an emerging discipline, it is a very dynamic area of research with many diverse viewpoints, whose future is yet to be determined.
A concept search is an automated information retrieval method that is used to search electronically stored unstructured text for information that is conceptually similar to the information provided in a search query. In other words, the ideas expressed in the information retrieved in response to a concept search query are relevant to the ideas contained in the text of the query.
Semantic audio is the extraction of meaning from audio signals. The field of semantic audio is primarily based around the analysis of audio to create some meaningful metadata, which can then be used in a variety of different ways.
Harmonic pitch class profiles (HPCP) is a group of features that a computer program extracts from an audio signal, based on a pitch class profile—a descriptor proposed in the context of a chord recognition system. HPCP are an enhanced pitch distribution feature that are sequences of feature vectors that, to a certain extent, describe tonality, measuring the relative intensity of each of the 12 pitch classes of the equal-tempered scale within an analysis frame. Often, the twelve pitch spelling attributes are also referred to as chroma and the HPCP features are closely related to what is called chroma features or chromagrams.
Sound and music computing (SMC) is a research field that studies the whole sound and music communication chain from a multidisciplinary point of view. By combining scientific, technological and artistic methodologies it aims at understanding, modeling and generating sound and music through computational approaches.
The International Society for Music Information Retrieval (ISMIR) is an international forum for research on the organization of music-related data. It started as an informal group steered by an ad hoc committee in 2000 which established a yearly symposium - whence "ISMIR", which meant International Symposium on Music Information Retrieval. It was turned into a conference in 2002 while retaining the acronym. ISMIR was incorporated in Canada on July 4, 2008.
Multimedia information retrieval is a research discipline of computer science that aims at extracting semantic information from multimedia data sources. Data sources include directly perceivable media such as audio, image and video, indirectly perceivable sources such as text, semantic descriptions, biosignals as well as not perceivable sources such as bioinformation, stock prices, etc. The methodology of MMIR can be organized in three groups:
- Methods for the summarization of media content. The result of feature extraction is a description.
- Methods for the filtering of media descriptions
- Methods for the categorization of media descriptions into classes.
The following outline is provided as an overview of and topical guide to natural-language processing:
ScoreCloud is a software service and web application for creating, storing, and sharing music notation, created by Doremir for macOS, Microsoft Windows, iPhone and iPad.
