Lloyd Smith

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An investigation into the use of machine learning for determining oestrus in cows

Computers and Electronics in Agriculture, 1996

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Practical machine learning and its application to problems in agriculture

One of the most exciting and potentially far-reaching developments in contemporary computer scien... more One of the most exciting and potentially far-reaching developments in contemporary computer science is the invention and application of methods of machine learning. These have evolved from simple adaptive parameter-estimation techniques to ways of (a) inducing classification rules from examples, (b) using prior knowledge to guide the interpretation of new examples, (c) using this interpretation to sharpen and refine the domain knowledge, and (d) storing and indexing example cases in ways that highlight their similarities and differences. Such techniques have been applied in domains ranging from the diagnosis of plant disease to the interpretation of medical test data. This paper reviews selected methods of machine learning with an emphasis on practical applications, and suggests how they might be used to address some important problems in the agriculture industries.

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Speech recognition using codebooks trained from a synthesized seed

The Journal of the Acoustical Society of America, 1989

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Optimisation techniques for a computer simulation of a pastoral dairy farm

Computers and Electronics in Agriculture, 1998

This paper compares different methods of optimising the management variables in UDDER, a commerci... more This paper compares different methods of optimising the management variables in UDDER, a commercially-available computer simulation model of a pastoral dairy farm. The emphasis is on identifying the best optimisation strategy for this complex multi-dimensional system, taking the simulation model as a given constant. The optimisation methods studied are based on significantly different principles, with differing strengths and weaknesses: two hill-climbing algorithms (Nelder-Mead Simplex and Powell's Direction Set), and a genetic algorithm. Rather than examine all facets of dairy farm management, a single problem is optimised-that of maximising milkfat production while maintaining the health of the herd and pasture. The results show that while the genetic algorithm can determine good regions within the search space quickly, it is considerably slower than either hill-climber at finding the optimal point within that region. The hillclimbers, in contrast, are fast but have a tendency to get trapped on local maxima and thus fail to find the true optimum. This led to the development of a hybrid algorithm which utilises the initial global search of the genetic algorithm, followed by the more efficient local search of a hill-climber. This hybrid algorithm discovered near-optimal points much more quickly than the genetic algorithm, and with more reliability than the hill-climber.

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Simplifying Dynamic Programming

Dynamic Programming (DP) is one of the fundamental topics usually covered in the algorithms cours... more Dynamic Programming (DP) is one of the fundamental topics usually covered in the algorithms course. Nonetheless, it is a challenging subject for many computer science students. This paper presents work in progress for making dynamic programming easier for students. We propose four simple and interesting DP problems that students can learn early in the curriculum. One of these problems can be introduced as early as CS1. The other problems can be used in a CS2 course. We believe that this will make the subject of DP easier for many students when they encounter it later, in an algorithms course, and will result in more success and retention of CS students.

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A sight-singing tutor

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A program to teach sight-singing

Proceedings of the Third International Technological Directions in Music Education Conference February 8 10 1996 1996 Pags 43 47, 1996

Improvements to a Sight-Singing Tutor

Proceedings of the Fourth International Technological Directions in Music Educacion Conference January 30 February 1 1997 1997 Pags 36 39, 1997

Data mining in sports: predicting Cy Young award winners

Journal of Computing Sciences in Colleges, Apr 1, 2007

A Bayesian classifier was created to predict Cy Young Award winners in American baseball. The mod... more A Bayesian classifier was created to predict Cy Young Award winners in American baseball. The model was compared against two statistical models designed to perform the same task. Over the years from 1967 through 2006, the accuracy of the Bayesian classifier was similar to that of the other two models---when restricted to starting pitchers, all three were more than 80% correct. Accuracy was lower for all three models when relief pitchers were included in the data.

Method and apparatus for generating a signal transformation and the use thereof in signal processing

Template adaptation in a hypersphere word classifier

International Conference on Acoustics, Speech, and Signal Processing

Two methods of adapting speech recognition templates for developing multispeaker or speaker-indep... more Two methods of adapting speech recognition templates for developing multispeaker or speaker-independent vocabularies are tested. Both methods rely on feedback to assess the accuracy of recognition, and both use the test utterance to modify the correct template when recognition fails. In addition, one method uses the test utterance to modify intruding templates, moving them away from the test token's position in pattern space; this method is more effective for developing both multispeaker and speaker-independent vocabularies

Practical machine learning and its potential application to problems in agriculture

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Content-based indexing of musical scores

2003 Joint Conference on Digital Libraries, 2003. Proceedings.

This paper describes a method of automatically creating a content-based index of musical scores. ... more This paper describes a method of automatically creating a content-based index of musical scores. The goal is to capture the themes, or motifs, that appear in the music. The method was tested by building an index of 25 orchestral movements from the classical music literature. For every movement, the system captured the primary theme, or a variation of the primary theme. In addition, it captured 13 of 28 secondary themes. The resulting index was 14% of the size of the database. A further reduction of 2% is possible; however, this discards secondary themes. A listening experiment using five orchestral movements showed that people can reliably recognize secondary themes after listening to a piece of music-therefore, it may be necessary to retain secondary themes in a score index.

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Towards the digital music library

Proceedings of the first ACM international conference on Digital libraries - DL '96, 1996

Music is traditionally retrieved by title, composer or subject classification. It is possible, wi... more Music is traditionally retrieved by title, composer or subject classification. It is possible, with current technology, to retrieve music from a database on the basis of a few notes sung or hummed into a microphone. This paper describes the implementation of such a system, and discusses several issues pertaining to music retrieval. We first describe an interface that transcribes acoustic input into standard music notation. We then analyze string matching requirements for ranked retrieval of music and present the results of an experiment which tests how accurately people sing well known melodies. The performance of several string matching criteria are analyzed using two folk song databases. Finally, we describe a prototype system which has been developed for retrieval of tunes from acoustic input.

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Evaluation of a melody transcription system

2000 IEEE International Conference on Multimedia and Expo. ICME2000. Proceedings. Latest Advances in the Fast Changing World of Multimedia (Cat. No.00TH8532)

... Each segmented note was inspected using a special purpose program incorporating the melody tr... more

Towards a digital library of popular music

Proceedings of the fourth ACM conference on Digital libraries - DL '99, 1999

Digital libraries of music have the potential to capture popular imagination in ways that more sc... more Digital libraries of music have the potential to capture popular imagination in ways that more scholarly libraries cannot. We are working towards a comprehensive digital library of musical material, including popular music. We have developed new ways of collecting musical material, accessing it through searching and browsing, and presenting the results to the user. We work with different representations of music: facsimile images of scores, the internal representation of a music editing program, page images typeset by a music editor, MIDI files, audio files representing sung user input, and textual metadata such as title, composer and arranger, and lyrics. This paper describes a comprehensive suite of tools that we have built for this project. These tools gather musical material, convert between many of these representations, allow searching based on combined musical and textual criteria, and help present the results of searching and browsing. Although we do not yet have a single fully-blown digital music library, we have built several exploratory prototype collections of music, some of them very large (100,000 tunes), and critical components of the system have been evaluated.

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Tune Retrieval in the Multimedia Library

Digital Libraries and Multimedia

Musical scores are traditionally retrieved by title, composer or subject classification. Just as ... more Musical scores are traditionally retrieved by title, composer or subject classification. Just as multimedia computer systems increase the range of opportunities available for presenting musical information, so they also offer new ways of posing musically-oriented queries. This paper shows how scores can be retrieved from a database on the basis of a few notes sung or hummed into a microphone. The design of such a facility raises several interesting issues pertaining to music retrieval. We first describe an interface that transcribes acoustic input into standard music notation. We then analyze string matching requirements for ranked retrieval of music and present the results of an experiment which tests how accurately people sing well known melodies. The performance of several string matching criteria are analyzed using two folk song databases. Finally, we describe a prototype system which has been developed for retrieval of tunes from acoustic input and evaluate its performance.

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Improvements to a speaker‐independent algorithm

The Journal of the Acoustical Society of America, 1989

Speech sounds generated by a simple waveform synthesizer were used to create a 16-vector codebook... more Speech sounds generated by a simple waveform synthesizer were used to create a 16-vector codebook for vector quantization (vq). This codebook was used as a seed for training over the TI-20 isolated word database, which was then used to test the resulting codebooks using speech recognition. The database was split into two sets of speakers and two codebooks were created for each set, one trained on one pass over the speech and the other trained iteratively. All codebooks were trained adaptively, resulting in codebooks of 31 vectors-16 high-energy and 15 low-energy vectors. Recognition was performed using a conventional DTW algorithm. The baseline recognition accuracy (using no vq) was 97%; the accuracy for the 16-vector synthesized codebook was 91.8%. Accuracy using trained codebooks ranged from 94% (two-sided vq) to 95.1% (one-sided vq with a normalized match distance). Crossing speaker sets (resulting in speaker-independent codebooks) yielded 94.9% recognition accuracy. The results indicate that speech synthesis can be used to decrease the training needed to develop multispeaker and speaker-independent codebooks.

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A computer model of blues music and its evaluation

The Journal of the Acoustical Society of America, 1996

This paper describes a new algorithm that composes blues melodies to fit a given chord sequence. ... more This paper describes a new algorithm that composes blues melodies to fit a given chord sequence. It comprises an analysis stage followed by a synthesis stage. The analysis stage produces a Markov model composed of zero, first‐, and second‐order transition tables covering both pitches and rhythms. In order to capture the relationship between harmony and melody, a set of transition tables is produced for each chord in the analyzed songs. The synthesis stage uses the output tables from analysis to generate new melodies; second‐order tables are used as much as possible, with fall back procedures to lower‐order tables. Some constraints are encoded in the form of rules to control the placement of rhythmic patterns within measures, pitch values for long duration notes and pitch values for the start of new phrases. The model was evaluated by a listening experiment; results showed that listeners were unable to reliably distinguish human from computer composed melodies.

Speech recognition using a synthesized codebook

The Journal of the Acoustical Society of America, 1988

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