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Neural Network-based Accent Classification Results

Module by: Scott Novich. E-mail the author

Summary: Listed in this module are output results and analysis of test-audio samples from various speakers, fed to a trained neural network.

Results

The following are some example outputs from the neural network from various test speakers. The output displays relative strengths of different types of accents prevalent in a particular subject. All test inputs were not used in the training matrix. Overall, approximately 20 tests were conducted with about an 80% success rate. Those that failed tended to with good reason (either inadequate recording quality, or speakers who did not provide accurate information about what their accent is comprised of – a common issue with subjects who have lived in multiple places).

The charts below show accents in the following order: Northern US, Texan US, Russian, Farsi, and Mandarin

Test 1: Chinese Subject

Figure 1: Chinese Subject (accent order: Northern US, Texan US, Russian, Farsi, and Mandarin)
Chinese Subject
Chinese Subject (test1-china-northeast.jpg)

Here our network has successfully picked out the accent of our subject. Secondarily, the network picked up on a slight Texan accent, possibly showing the influence of location on the subject (The sample was recorded in Texas).

Test 2: Iranian Subject

Figure 2: Iranian Subject (accent order: Northern US, Texan US, Russian, Farsi, and Mandarin)
Iranian Subject
Iranian Subject (test2-farsi-11.jpg)
Audio File: test2-farsi-11.mp3

Again our network has successfully picked out the accent of our subject. Once again, this sample was recorded in Texas, which could account for the secondary influence of a Texan accent in the subject.

Test 3: Chinese Subject

Figure 3: Chinese Subject (accent order: Northern US, Texan US, Russian, Farsi, and Mandarin)
Chinese Subject
Chinese Subject (test3-mandarin-6.jpg)

Once again, the network successfully picks up on the subjects primary accent as well as influence of a Texan accent (this sample was also recorded in Texas).

Test 4: Chinese Subject

Figure 4: Chinese Subject (accent order: Northern US, Texan US, Russian, Farsi, and Mandarin)
Chinese Subject
Chinese Subject (test4-mandarin-10.jpg)

A successful test showing little or no influence from other accents in the network.

Test 5: American Subject (Hybrid of Regions)

Figure 5: American Subject - Hybrid (accent order: Northern US, Texan US, Russian, Farsi, and Mandarin)
American Subject (Hybrid)
American Subject (Hybrid) (test5-northern-test-7.jpg)

Results from a subject who has lived all over -- mainly in Texas, who's accent appears to sound more Northern (which seems relatively true if one listens to the source recording).

Test 6: Russian Subject

Figure 6: Russian Subject (accent order: Northern US, Texan US, Russian, Farsi, and Mandarin)
Russian Subject
Russian Subject (test6-russian-8.jpg)

Successful test of a Russian subject with strong influences of a Northern US accent.

Test 7: Russian Subject

Figure 7: Russian Subject (accent order: Northern US, Texan US, Russian, Farsi, and Mandarin)
Russian Subject
Russian Subject (test7-russian-test-8.jpg)

Another successful test of a Russian subject with strong influences of a Northern US accent.

Test 8: Cantonese Subject

Figure 8: Cantonese Subject (accent order: Northern US, Texan US, Russian, Farsi, and Mandarin)
Cantonese Subject
Cantonese Subject (test8-wai-lam1.jpg)
Audio File: test8-wai-lam.mp3

Successful region-based test of a Cantonese subject who has been living in the US.

Test 1: Korean Subject

Figure 9: Korean Subject (accent order: Northern US, Texan US, Russian, Farsi, and Mandarin)
Korean Subject
Korean Subject (test9-korean-3.jpg)
Audio File: test9-korean-3.mp3

An interesting example of throwing an accent at the network that doesn't fit into any of the categories.

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