Guide-linked quiz · Medium Level
AI in Call Center Speech Analytics Quiz
Test speech recognition, diarization, and sentiment analysis in call-center research, including the limits and scope of each cited study.
Question 1 of 8
What output can automatic speech recognition provide for speech analytics?
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- What output can automatic speech recognition provide for speech analytics?
- A machine-generated transcript for downstream text analysis
- A guaranteed speaker identity
- A final diagnosis of the caller’s emotional state
- A payment authorization
- What does speaker diarization do in a call recording?
- Translates the call into another language
- Segments the recording into speaker turns and assigns speaker labels
- Measures how loud the call was
- Encrypts the recording
- In IBM’s two-stream call-center emotion-recognition study, which information streams are combined?
- Video and keystroke timing
- Customer purchase history and account balance
- Acoustic and lexical information
- Only transcript punctuation
- Which acoustic feature helps detect a customer's emotional state beyond the words used?
- File size of the recording
- The agent's employee ID
- The phone carrier
- Pitch, pace, and volume (prosody)
- In a two-stream call-center emotion system, what do acoustic features contribute?
- Evidence from vocal delivery, such as how speech sounds
- The caller’s verified identity
- The account’s payment history
- A guaranteed diagnosis of the caller’s emotion
- What task did Vidrascu and Devillers study for customer-service phone calls?
- Predicting credit scores from call recordings
- Speaker segmentation and emotion-related analysis of conversational turns
- Generating live agent sales recommendations
- Automating legal decisions about customer accounts
- Why might a call-center sentiment system combine lexical and acoustic features?
- Acoustic features replace the transcript in every task
- Lexical features reveal the phone carrier
- The words and the way they are spoken provide complementary signals
- Combining them guarantees the caller’s true emotion is known
- What does word-error rate compare in speech recognition evaluation?
- Speaker identity against a customer account
- Emotion labels against call duration
- Call volume against agent schedule
- Substitutions, deletions and insertions against the words in a reference transcript
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