Abstract:
This paper describes a retrieval method for a significant amount of music tracks. It takes a melody sung or a text input as a search clue which is sent over the internet to retrieve the song from the database. This system uses a variety of procedures to support multiple search modes. The thorough indexing method allows for rapid recovery of the song. Integration of these components within a single architecture shall improve performance and functionality.
Overview of Objectives:
The aim of this paper is to utilise and develop existing techniques for Music Information Retrieval. The system shall be able to retrieve a song from either a text query or a melody query. This melody can be sung, a riff or humming. Browsing the database shall also be available to the user. The database shall reside on a server. For the purposes of this paper, it shall contain 10,000 songs. However, taking into consideration all the features of this system, I would expect it to be able to process a database 1000% larger.
Text
Query
Search Engines
Text Matching
Theme Matching
Phonetic Matching
Markov Representation
Music
Archive
User
Interface
Aural
Query
Figure 1 Name That Tune Architecture
Functional Description of the System:
The system shall have a graphical interface containing 2 search engines:
1. Text Input User may enter the title, line of song, artist
2. Aural Input User may sing, hum, play a riff
The user would choose their preferable search method.
The aural input is processed through a Speech Recognition System. This comprises of 2 components:
1. An acoustic model using statistical modelling using hidden Markov models. 2. A language model model of the expected word sequences. This vocabulary will contain 80,000 words.
The songs shall be contained in a database with a corresponding value recorded in an index. This would contain 4 sections:
1. Traditional Text Matching
2. Theme Matching
3. Phonetic Matching
4. Markov Representation
There are other techniques, but after researching I feel that these are the most productive.
Sections 1 and 2 deal with the Text Input and 3 and 4 with the Aural Input. The file structure shall be that of the inverted file. This stores term locations. It shall also include term proximity. The most effective method to compute term locations is to use a hashing algorithm which will be employed in this system.
As all lyrics shall be recorded with each song, the Text Matching search shall be the most accurate. However, many users may not input the correct words and incorrect songs would be displayed.
This method shall use general information retrieval techniques.
materials. The song pluggers could improvise and transpose a song on the spot to fit a
Polyphonic HMI, a subdivision of Barcelona-based Grupo AIA, is charged with applying the parent company’s artificial intelligence and natural science ideas and products to the music industry. Grupo’s major strengths lie in these areas and have led to the development of several successful and innovative tools used to solve all types of business problems across different industry sectors. Polyphonic, Grupo’s first entertainment-based subsector, is releasing Hit Song Science (hereafter HSS), a software used to predict the potential success of songs by mapping their mathematical properties and matching those to previous hits. However, Polyphonic is facing a series of problems. Two stand out: one, they have no identifiable target market. Two, Polyphonic has no defined marketing approach on which to launch their original product offering. This report will address, analyze and make recommendations for solving these challenges.
Most users will find what they are looking for the first times when conducting searches due to the database sufficiently being able to decode natural language. As users navigate through the website they will find many icons and tabs to help them through their searches. One does not have to be an expert to conduct searches using this database and will be able to use the simple search index to retrieve a desirable number of sources if the user knows exactly what they are trying to retrieve. This database would be an essential tool for students, teachers, or any patron to meet their informational
Music plays an integral part in shaping peoples lives, its effects people in a multitude of different ways, whether it be dancing, laughing or crying; most incredibly people can share these moments with others whilst simultaneously having a unique personal experience. The creation of music requires specific skills and knowledge about musical elements and instrumentation; these skills and knowledge need to be developed and nurtured over time.
Popular music places a premium on accessibility, represents various meanings to boost both instant appeal and memorability - distinctive tunes, novel instrumental flourishes, danceable rhythms, repeated riffs - but its signal feature is melodic emphasis and great vocal gatherings.
Before the 1990’s, if people want to listen to music, they just visit a music store and pick up a CD and then put it into a stereo equipment. However, the development of MP3 file format gradually changed the way people listen to music. This format lets everyone download music easily and it can be converted to CD as well. But, there is still a problem: searching MP3 files on the internet is maddening and people seldom can find the music they want. Therefore, the birth of Napster solved this problem, creating a virtual music community in which music fans could use the Web as a “swap meet” for music files. More importantly, Napster is easy to use and it’s free, which expands the range of audience in age. Bandwidth also contributed to Napster’s success. The greater the bandwidth, the faster the file can be transferred. So, Napster really changed the way people listen to music, discover music and interact with music.
Vicars, W., Ed.D. (1997-2013). ASL Classifiers Level 1. Lifeprint.com. Retrieved February 16, 2014, from http://www.lifeprint.com/asl101/pages-signs/classifiers/classifiers-frame.htm
Our life is a fantastic journey made all the better with great music. If you’ve got a huge collection of music and playlists, you may want to transfer them to various devices, edit the track and album information and (most importantly) be able to play them whenever you want. I put together a list of the top music management software solutions to help you to customize your music library.
Find a figure of speech from your song. Copy it here and identify what types of figure of speech it is. Explain what it means.
Song is an art that having created from a combination of word known as lyrics and rythem to ensure the beautiful melody. According to Allan (2014), people’s attitude are affected by their favourite song. People tend to have calmness when listening to music. Chen and Chen (2009) state that listening to the English song is considered as one of the effective teaching style to motivate elementary school students to learning English. People have a different taste of music. They can find the excitement of music through a different genre such as a cappella song, ballad song and nasyid song.
There are two main theories of Speech production, Spreading Activation Theory - SAT (Dell, 1986: Dell & O’Seaghdha, 1991) and Word- Form Encoding by Activation and Verification – WEAVER++ (Levelt et al., 1989: 1999).
Speech perception is the ability to comprehend speech through listening. Mankind is constantly being bombarded by acoustical energy. The challenge to humanity is to translate this energy into meaningful data. Speech perception is not dependent on the extraction of simple invariant acoustic patterns in the speech waveform. The sound's acoustic pattern is complex and greatly varies. It is dependent upon the preceding and following sounds (Moore, 1997). According to Fant (1973), speech perception is a process consisting of both successive and concurrent identification on a series of progressively more abstract levels of linguistic structure.
The average consumer may download songs or articles from the Internet, but they do not distribute them or reproduce them. If they do reproduce them it is usually for personal use. The MP3 player that ...
Argabright, R (Winter, 2005). Connecting with music. General Music Today, 18(2)5. Retrieved May 15, 2005, from EBSCO research database.
Jurafsky, D. & Martin, J. H. (2009), Speech and Language Processing: International Version: an Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition, 2nd ed, Pearson Education Inc, Upper Saddle River, New Jersey.