Relevant bibliographies by topics / The Singing Detective

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'The Singing Detective'

Author: Grafiati
Published: 4 June 2021
Last updated: 19 February 2022

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Journal articles on the topic "The Singing Detective"

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Gontarski, S. E. "The Singing Detective Plays Beckett (Again)." Journal of Beckett Studies 15, no. 1-2 (January 2005): 242–47. http://dx.doi.org/10.3366/jobs.2006.15.1-2.21.

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Gras, Vernon. "Revisiting The Singing Detective decades later." Journal of Screenwriting 4, no. 3 (August 1, 2013): 305–7. http://dx.doi.org/10.1386/josc.4.3.305_7.

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Aubry, Danielle. "The Singing Detective: Dédales agonistiques d'une rédemption." University of Toronto Quarterly 73, no. 3 (July 2004): 847–61. http://dx.doi.org/10.3138/utq.73.3.847.

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Ganz, Adam. "Interview with Jon Amiel, Director of The Singing Detective." Journal of Screenwriting 4, no. 3 (August 1, 2013): 227–36. http://dx.doi.org/10.1386/josc.4.3.227_7.

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Cook, John R. "‘Message for Posterity’: The Singing Detective (1986) 25 years on." Journal of Screenwriting 4, no. 3 (August 1, 2013): 259–72. http://dx.doi.org/10.1386/josc.4.3.259_1.

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Kenneth Pellow, C. "The Function of “The Bloody Songs” in Dennis Potter's The Singing Detective." Journal of Popular Culture 46, no. 5 (October 2013): 1051–69. http://dx.doi.org/10.1111/jpcu.12066.

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Vickers, N. "Religious Irony and Freudian Rationalism in Dennis Potter's The Singing Detective (1986)." Literature and Theology 20, no. 4 (October 30, 2006): 411–23. http://dx.doi.org/10.1093/litthe/frl041.

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Corrigan, Timothy. "Back to the future in The Singing Detective: Amphibians, puzzles, and adaptations." Journal of Screenwriting 4, no. 3 (August 1, 2013): 237–45. http://dx.doi.org/10.1386/josc.4.3.237_7.

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Creeber, Glen. "And the beat goes on: The continuing influence of The Singing Detective." Journal of Screenwriting 4, no. 3 (August 1, 2013): 247–58. http://dx.doi.org/10.1386/josc.4.3.247_1.

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Qureshi, Faisal A. "The Singing Detective goes to Hollywood: An interview with director Keith Gordon." Journal of Screenwriting 4, no. 3 (August 1, 2013): 325–33. http://dx.doi.org/10.1386/josc.4.3.325_7.

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Dissertations / Theses on the topic "The Singing Detective"

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Evans, Gwynne Wheldon. "Out of the Limelight (a Cycle of Plays) and The Singing Detective and Out of the Limelight: a Comparative Study." Thesis, Bangor University, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.490423.

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This Ph.D. in Creative and Critical Writing is presented in two parts. The first part consists of a cycle of four original teleplays entitled Out of the Limelight, portraying the experiences of members of a theatre company. The main character in each case is drawn into a world of constructed realism. Each character reacts in an individualistic way, in accordance with their purpose. In some cases there is a remedy, brought about by the character himself or by an outside force. Sometimes a combination of both is required. In one case the result is tragic. The second part of the Ph.D., a critical
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Brie, Stephen Michael. "'Yesterday once more' : an investigation of the relationship between popular music, audience, and authorial intention in Dennis Potter's 'Pennies from heaven', 'The singing detective', and 'Lipstick on your collar'." Thesis, University of Liverpool, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.250379.

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Critical interpretations of Dennis Potter's television drama serials have tended to take a writer-centred perspective, focusing on establishing links between the dramatist's life and work. In analysing the popular music content of these texts, critics have consistently postulated the existence of Brechtian distanciation effects on an implied viewer. Although, in order to contextualise Potter's relationship with popular music, authorial intention is discussed, this study shifts the focus towards empirical interpretations of the musical sequences in Pennies from Heaven, The Singing Detective and
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Nolan, Karin. "The Comparative Effectiveness of Teaching Beat Detection through Movement and Singing among Kindergarten Students." Thesis, The University of Arizona, 2007. http://hdl.handle.net/10150/193302.

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The purpose of this study was to determine if beat detection and beat competency (i.e. maintaining a steady beat) could be more effectively taught through movement, singing, or a combination of the two. Subjects (N =102) were kindergarten students from an elementary school in the Southwest. Students completed a pretest and posttest to assess beat detection ability; the test measured their ability to tap a steady beat with and without music. Subjects received instruction in one of three methods for a six-week period: singing, movement, or a combination of the two. Data analysis results revealed
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Milo, Sarah Khatcherian. "Guide of the Voice Teacher to Vocal Health for Voice Students: Preventing, Detecting, and Addressing Symptoms." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1399019362.

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Werder, Dominik. "Color Screening in QCD and Neutrinos from Singlino Dark Matter." Doctoral thesis, Uppsala universitet, Högenergifysik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-267310.

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Hard diffraction in proton collisions, where the initial state proton emerges from the interaction rather undisturbed despite a hard interaction scale, has been studied for a few decades. First observed in proton-proton collisions, the phenomenon is seen as well in deep inelastic electron-proton scattering (DIS) as a leading final state proton and a rapidity gap-region without final state particles. Although a rather successful description in terms of the exchange of a hadronic color singlet pomeron with a parameterized gluon content exists, it is still an open question whether a theoretically
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Gong, Rong. "Automatic assessment of singing voice pronunciation: a case study with Jingju music." Doctoral thesis, Universitat Pompeu Fabra, 2018. http://hdl.handle.net/10803/664421.

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Online learning has altered music education remarkable in the last decade. Large and increasing amount of music performing learners participate in online music learning courses due to the easy-accessibility and boundless of time-space constraints. Singing can be considered the most basic form of music performing. Automatic singing voice assessment, as an important task in Music Information Retrieval (MIR), aims to extract musically meaningful information and measure the quality of learners' singing voice. Singing correctness and quality is culture-specific and its assessment requires cu
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Allegro, Pedro Luís Cameira Sollari. "Singing voice detection in polyphonic music signals." Dissertação, 2008. http://hdl.handle.net/10216/57980.

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Estágio realizado no INESC e orientado pelo Prof. Fabien Gouyon<br>Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores (Ramo Telecomunicações). Faculdade de Engenharia. Universidade do Porto. 2008
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Allegro, Pedro Luís Cameira Sollari. "Singing voice detection in polyphonic music signals." Master's thesis, 2008. http://hdl.handle.net/10216/57980.

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Estágio realizado no INESC e orientado pelo Prof. Fabien Gouyon<br>Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores (Ramo Telecomunicações). Faculdade de Engenharia. Universidade do Porto. 2008
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Liu, Chih-Chun, and 劉至峻. "Deep Learning Algorithm Using Multi-model Combination Applied to Singing Voice Detection." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/4f4um8.

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碩士<br>國立臺北科技大學<br>資訊工程系<br>106<br>Detecting the vocal sound in a piece of audio is a fundamental step to many advanced audio processing techniques. Previously, one study showed that good accuracy of 92% could be achievable for this problem by using the convolutional neural networks (CNN) using spectrogram as the input features. To explore the possibilities of further performance improvement, in this thesis we attempted to incorporate CNN and other neural network architectures, such as Long Short Term Memory (LSTM), Convolutional LSTM, and Capsule Networks, into ensemble learning. The ensemble
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Huang, Hsin-Jung, and 黃信榮. "A Study on Note Detection and Melody Matching Method for Query By Singing/Humming System." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/01357850967450510157.

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碩士<br>國立臺灣科技大學<br>資訊管理系<br>97<br>Onset detection for singing voices is an important but difficult problem for note detection in query by singing/humming or music transcription. The purpose of this paper is to improve the performance of onset detection for singing/humming voice. This paper proposes an onset detection scheme which utilizes the moving average filtering in detection function to accentuate the uprising margins, while making use of discriminative classifier based on Gaussian mixture models to combine relevant features of adjacent peaks in final decision. Experimental results show th
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Books on the topic "The Singing Detective"

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Potter, Dennis. The singing detective. New York: Vintage Books, 1986.

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The singing detective. New York: Vintage Books, 1988.

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Potter, Dennis. The singing detective. New York: Vintage Books, 1988.

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The singing detective. London: Faber and Faber, 1986.

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Potter, Dennis. The singing detective: [screenplay]. London: Hollywood Scripts, 1990.

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The singing cave. Swords: Children's Poolbeg, 1991.

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Whitney, Phyllis A. The singing stones. London: Hodder & Stoughton, 1990.

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Whitney, Phyllis A. The singing stones. London: Coronet, 1991.

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Whitney, Phyllis A. The singing stones. London: Chivers, 1992.

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Whitney, Phyllis A. The singing stones. New York: Doubleday, 1990.

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Book chapters on the topic "The Singing Detective"

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Voigts-Virchow, Eckart. "Potter, Dennis: The Singing Detective." In Kindlers Literatur Lexikon (KLL), 1–2. Stuttgart: J.B. Metzler, 2020. http://dx.doi.org/10.1007/978-3-476-05728-0_14515-1.

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Miyagawa, Isao, Yuya Chiba, Takashi Nose, and Akinori Ito. "Detection of Singing Mistakes from Singing Voice." In Advances in Intelligent Information Hiding and Multimedia Signal Processing, 130–36. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63859-1_17.

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You, Shingchern D., and Yi-Chung Wu. "Comparative Study of Singing Voice Detection Methods." In Computer Science and its Applications, 1291–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-45402-2_180.

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Rao, Vishweshwara, Chitralekha Gupta, and Preeti Rao. "Context-Aware Features for Singing Voice Detection in Polyphonic Music." In Adaptive Multimedia Retrieval. Large-Scale Multimedia Retrieval and Evaluation, 43–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37425-8_4.

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Chen, Zhigao, Xulong Zhang, Jin Deng, Juanjuan Li, Yiliang Jiang, and Wei Li. "A Practical Singing Voice Detection System Based on GRU-RNN." In Lecture Notes in Electrical Engineering, 15–25. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8707-4_2.

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Stoller, Daniel, Sebastian Ewert, and Simon Dixon. "Jointly Detecting and Separating Singing Voice: A Multi-Task Approach." In Latent Variable Analysis and Signal Separation, 329–39. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93764-9_31.

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Zhang, Xulong, Shengchen Li, Zijin Li, Shizhe Chen, Yongwei Gao, and Wei Li. "Singing Voice Detection Using Multi-Feature Deep Fusion with CNN." In Lecture Notes in Electrical Engineering, 41–52. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-2756-2_4.

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Rocamora, Martín, and Alvaro Pardo. "Separation and Classification of Harmonic Sounds for Singing Voice Detection." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 707–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33275-3_87.

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Mimilakis, Stylianos I., Christof Weiss, Vlora Arifi-Müller, Jakob Abeßer, and Meinard Müller. "Cross-version Singing Voice Detection in Opera Recordings: Challenges for Supervised Learning." In Machine Learning and Knowledge Discovery in Databases, 429–36. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43887-6_35.

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Neocleous, Andreas, George Azzopardi, Christos N. Schizas, and Nicolai Petkov. "Filter-Based Approach for Ornamentation Detection and Recognition in Singing Folk Music." In Computer Analysis of Images and Patterns, 558–69. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23192-1_47.

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Conference papers on the topic "The Singing Detective"

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Moura, Shayenne, and Marcelo Queiroz. "Instrumental Sensibility of Vocal Detector Based on Spectral Features." In Simpósio Brasileiro de Computação Musical. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/sbcm.2019.10451.

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Detecting voice in a mixture of sound sources remains a challenging task in MIR research. The musical content can be perceived in many different ways as instrumentation varies. We evaluate how instrumentation affects singing voice detection in pieces using a standard spectral feature (MFCC). We trained Random Forest models with song remixes for specific subsets of sound sources, and compare it to models trained with the original songs. We thus present a preliminary analysis of the classification accuracy results.
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Shenoy, Arun, Yuansheng Wu, and Ye Wang. "Singing voice detection for karaoke application." In Visual Communications and Image Processing 2005. SPIE, 2005. http://dx.doi.org/10.1117/12.631645.

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Nwe, Tin Lay, Arun Shenoy, and Ye Wang. "Singing voice detection in popular music." In the 12th annual ACM international conference. New York, New York, USA: ACM Press, 2004. http://dx.doi.org/10.1145/1027527.1027602.

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Paul, Soumava, Gurunath Reddy M, K. Sreenivasa Rao, and Partha Pratim Das. "Knowledge Distillation for Singing Voice Detection." In Interspeech 2021. ISCA: ISCA, 2021. http://dx.doi.org/10.21437/interspeech.2021-636.

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Leonidas, Ioannidis, and Jean-Luc Rouas. "Exploiting Semantic Content for Singing Voice Detection." In 2012 IEEE Sixth International Conference on Semantic Computing (ICSC). IEEE, 2012. http://dx.doi.org/10.1109/icsc.2012.18.

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Tsai, Wei-Ho, Van-Thuan Tran, and Shiang-Shiun Kung. "Automatic Detection of Mispronounced Lyrics in Singing." In 2019 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE, 2019. http://dx.doi.org/10.1109/icmlc48188.2019.8949315.

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Nwe, Tin Lay, and Haizhou Li. "Singing voice detection using perceptually-motivated features." In the 15th international conference. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1291233.1291299.

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Pikrakis, Aggelos, Yannis Kopsinis, Nadine Kroher, and Jose-Miguel Diaz-Banez. "Unsupervised singing voice detection using dictionary learning." In 2016 24th European Signal Processing Conference (EUSIPCO). IEEE, 2016. http://dx.doi.org/10.1109/eusipco.2016.7760441.

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Lin, Tse-En, Chung-Chien Hsu, Yi-Cheng Chen, Jian-Hueng Chen, and Tai-Shih Chi. "Spectro-temporal modulation based singing detection combined with pitch-based grouping for singing voice separation." In Interspeech 2013. ISCA: ISCA, 2013. http://dx.doi.org/10.21437/interspeech.2013-652.

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Leglaive, Simon, Romain Hennequin, and Roland Badeau. "Singing voice detection with deep recurrent neural networks." In ICASSP 2015 - 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2015. http://dx.doi.org/10.1109/icassp.2015.7177944.

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