Google Exam Professional Machine Learning Engineer Topic 5 Question 86 Discussion

Actual exam question for Google's Professional Machine Learning Engineer exam

Question #: 86
Topic #: 5

[All Professional Machine Learning Engineer Questions]

You work at an organization that maintains a cloud-based communication platform that integrates conventional chat, voice, and video conferencing into one platform. The audio recordings are stored in Cloud Storage. All recordings have an 8 kHz sample rate and are more than one minute long. You need to implement a new feature in the platform that will automatically transcribe voice call recordings into a text for future applications, such as call summarization and sentiment analysis. How should you implement the voice call transcription feature following Google-recommended best practices?

AUse the original audio sampling rate, and transcribe the audio by using the Speech-to-Text API with synchronous recognition.

BUse the original audio sampling rate, and transcribe the audio by using the Speech-to-Text API with asynchronous recognition.

CUpsample the audio recordings to 16 kHz. and transcribe the audio by using the Speech-to-Text API with synchronous recognition.

DUpsample the audio recordings to 16 kHz. and transcribe the audio by using the Speech-to-Text API with asynchronous recognition.

Show Suggested Answer

Suggested Answer: D

by Raylene at Sep 12, 2024, 01:17 PM

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Galen

3 months ago

I see your point, Alba. Let's go with the original rate for now.

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Erasmo

3 months ago

I'm with the crowd on this one. Option D is the way to go. Though I do wonder if the audio quality will be as good as a human transcriptionist. Maybe we should hire some really bored linguists instead?

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Kasandra

2 months ago

User 3: Hiring linguists might be a good idea for quality control, but automating the transcription with Option D is more efficient.

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Lanie

3 months ago

I agree, using asynchronous recognition with the Speech-to-Text API will also speed up the transcription process.

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Katheryn

3 months ago

Option D is definitely the best choice. Upsampling the audio to 16 kHz will improve the transcription accuracy.

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Alba

4 months ago

That's a good point, but I think using the original rate is more efficient.

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Reta

4 months ago

But wouldn't upsampling to 16 kHz improve the transcription accuracy?

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Margurite

4 months ago

Haha, I'm just imagining the poor interns having to listen to all those long, boring call recordings. Good thing they've got the Speech-to-Text API to do the dirty work!

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Frederick

3 months ago

D) Upsample the audio recordings to 16 kHz. and transcribe the audio by using the Speech-to-Text API with asynchronous recognition.

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Sueann

3 months ago

C) Upsample the audio recordings to 16 kHz. and transcribe the audio by using the Speech-to-Text API with synchronous recognition.

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Maile

3 months ago

B) Use the original audio sampling rate, and transcribe the audio by using the Speech-to-Text API with asynchronous recognition.

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Alyce

3 months ago

A) Use the original audio sampling rate, and transcribe the audio by using the Speech-to-Text API with synchronous recognition.

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Galen

4 months ago

I agree with Alba, using the original rate seems like the best option.

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Curt

4 months ago

Option D all the way! 16 kHz audio and async recognition - that's the way to go. Gotta love those Google best practices, am I right?

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Lai

4 months ago

I agree with Antonio. The Google-recommended best practices suggest using asynchronous recognition for longer audio files, and upsampling to 16 kHz will improve the accuracy of the transcription.

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Antonio

4 months ago

Option D seems like the best choice here. Upsampling to 16 kHz and using asynchronous recognition will likely give us the best results for long audio recordings.

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Elli

3 months ago

Definitely, implementing this new feature will enhance the platform's capabilities for users.

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Dalene

3 months ago

It's important to follow best practices to ensure accurate transcriptions for future applications.

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Denny

3 months ago

Agreed, asynchronous recognition will also help with processing longer audio recordings more efficiently.

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Daniel

3 months ago

Great, let's go with option D then. It seems like the most effective approach for implementing the voice call transcription feature.

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Carmen

4 months ago

I agree, using asynchronous recognition will also help with processing longer audio recordings more efficiently.

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Kirk

4 months ago

I think option D is the way to go. Upsampling to 16 kHz should improve the transcription accuracy.

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Blossom

4 months ago

I think option D is the way to go. Upsampling to 16 kHz should improve transcription accuracy.

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Alba

4 months ago

I think we should use the original audio sampling rate for transcription.

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