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Evaluation of classification techniques for audio indexing ...
https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.378.8698#:~:text=This%20work%20compares%20two%20classification%20techniques%20used%20in,SVM%20in%20terms%20of%20accuracy%20and%20execution%20time.
EVALUATION OF CLASSIFICATION TECHNIQUES FOR AUDIO …
http://signal.ee.bilkent.edu.tr/defevent/papers/cr1966.pdf
This work compares two classification techniques used in audio indexing tasks: Gaussian Mixture Models (GMM) and Support Vector Machines (SVM). GMM is a classical technique taken as reference for comparing the performance of SVM in terms of accuracy and execution time. For testing the methodologies, we perform speech
Evaluation of classification techniques for audio indexing ...
https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.378.8698
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): This work compares two classification techniques used in audio indexing tasks: Gaussian Mixture Models (GMM) and Support Vector Machines (SVM). GMM is a classical technique taken as reference for comparing the performance of SVM in terms of accuracy and execution time.
Audio Segmentation and Classification
http://www2.imm.dtu.dk/pubdb/edoc/imm3851.pdf
The classification methods used include the General Mixture Model (GMM) and the k- Nearest Neighbour (k-NN) algorithms. It is shown that the system implemented achieves an accuracy rate of more than 95% for discrete audio classification. Keywords: audio content analysis, segmentation, classification, GMM, k-NN, MFCC, ZCR, STE and MPEG v
Indexing and Retrieval of Audio: A Survey | SpringerLink
https://link.springer.com/article/10.1023/A:1012491016871
This paper provides a comprehensive survey of audio indexing and retrieval techniques. We first describe main audio characteristics and features and discuss techniques for classifying audio into speech and music based on these features. Indexing and retrieval of speech and music is then described separately. Finally, significance of audio in multimedia indexing and retrieval is …
Audio indexing: primary components retrieval | SpringerLink
https://link.springer.com/article/10.1007/s11042-006-0027-1
Our purpose is to detect and locate sound unity to structure the audio dataflow in program broadcasts (reports). We present two audio classification tools that we have developed. The first one, a speech music classification tool, is based on three original features: entropy modulation, stationary segment duration (with a Forward–Backward Divergence algorithm) and …
Evaluation of Classification Model Accuracy: Essentials ...
http://www.sthda.com/english/articles/36-classification-methods-essentials/143-evaluation-of-classification-model-accuracy-essentials/
Evaluation of Classification Model Accuracy: Essentials. After building a predictive classification model, you need to evaluate the performance of the model, that is how good the model is in predicting the outcome of new observations test data that have been not used to train the model. In other words you need to estimate the model prediction ...
The 5 Classification Evaluation metrics every Data ...
https://towardsdatascience.com/the-5-classification-evaluation-metrics-you-must-know-aa97784ff226
A. Accuracy. Accuracy is the quintessential classification metric. It is pretty easy to understand. And easily suited for binary as well as a multiclass classification problem. Accuracy = (TP+TN)/ (TP+FP+FN+TN) Accuracy is the proportion of true results among the total number of cases examined.
Common Classification Model Evaluation metrics. | by …
https://towardsdatascience.com/common-classification-model-evaluation-metrics-2ba0a7a7436e
Common Classification Model Evaluation metrics. ... First I will fit a simple model and use it to illustrate these methods are applied in model performance evaluation. The model predicts whether a cancerous cell is malignant or not. ... The idea behind this index is that higher the similarity of these two groups the higher the index.
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