INDEPENDENT RECORDING ANALYSIS

Voice AI sounds human.
Show the evidence.

We were as excited as you about Dessa. So we built a concept to explore how audio could be tested with QualityMax.

Listen to the published conversation, explore who speaks when, and inspect measured changes in the recording. Some questions still need a human ear.

A QualityMax research prototype · Recorded audio, analyzed offline

THE AUDIBILITY EXCHANGE02:02—02:48
SELECTED RESPONSE WINDOWS
2:022:172:332:48
First comparisonLater comparison
FIRST COMPARISON−4.3 dB

Quieter selected window

LATER COMPARISON+5.0 dB

Louder selected window

PRESS PLAY / FOLLOW THE VOICES

Hear the recording.

The original audio from the linked X recording, at its original level. Playback follows the speaker timeline below.

Source: linked X recording / Block’s Dessa conversation. Anonymous speaker labels are model estimates. Source attribution ↗

Read the conversation transcript

Text from Block’s published conversation captions, aligned to this recording. Voice numbers follow the publisher’s labels, separately from our estimated speaker clusters. Captions may contain errors and omit non-speech sounds.

Voice 1: Hey, how you doing?

Voice 2: I'm doing well.

Voice 2: How are you doing with the winter

Voice 2: stuff?

Voice 1: Winter is coming for sure, but you

Voice 1: know

Voice 2: Is that kind of a sore spot

Voice 2: this year?

Voice 1: Yeah, it's gonna be cold that I'm

Voice 1: not a fan of the snow I

Voice 1: prefer to have sun on my skin.

Voice 1: You know what I'm saying?

Voice 2: Yeah, I can see that.

Voice 1: Well, anyway, I've had such an exciting

Voice 1: day at work today.

Voice 2: Oh, tell us.

Voice 1: Yeah, we the team

Voice 1: We've decided to release the speech-to

Voice 1: -speech AI model we've built for the

Voice 1: past year and

Voice 2: Whoa.

Voice 2: Whoa.

Voice 2: So I have been watching your journey

Voice 2: of creating this.

Voice 1: What did you think of it?

Voice 1: Are you excited about it as much

Voice 2: I was so blown away.

Voice 1: as I am?

Voice 2: I am so impressed, to be honest.

Voice 1: Yeah, it's so expressive, right?

Voice 2: It is so expressive, it, it's

Voice 2: conversational it's

Voice 1: It's it's it's very conversational.

Voice 1: It can laugh.

Voice 1: It can understand you and your emotions

Voice 1: much better than anything I've seen out

Voice 1: there.

Voice 2: I haven't really seen

Voice 2: anything like that either but it's it's

Voice 2: pretty much like human level.

Voice 1: Yeah, it's a bit scary, to be

Voice 1: honest,

Voice 1: but

Voice 1: but I'm so excited to see where

Voice 1: it would get us.

Voice 2: I'm

Voice 2: so

Voice 2: excited for it to be in the

Voice 2: world because it's just amazing we've had

Voice 1: I know.

Voice 2: so

Voice 1: So I totally agree.

Voice 2: many conversations about it.

Voice 1: What are you excited for?

Voice 1: What's your vision for where this AI

Voice 1: is going to be?

Voice 2: I, well, okay, so the one thing

Voice 2: that I've been kind of

Voice 2: about is advertising companies creating

Voice 2: their own AI bot.

Voice 1: No, fuck advertising.

Voice 1: If you were able to talk to

Voice 1: this AI, what will you tell it?

Voice 2: Oh, I would ask it so

Voice 1: What would you ask it?

Voice 2: many questions so if it could be

Voice 1: Like what?

Voice 2: talking it I don't know off the

Voice 2: bat I would ask

Voice 2: it for all the secrets

Voice 2: like

Voice 1: Like what secrets?

Voice 2: I would honestly ask it like what

Voice 1: Sorry, you're a bit far from the

Voice 2: is

Voice 2: consciousness I

Voice 1: mic.

Voice 1: Can you come closer so I can

Voice 1: hear you?

Voice 2: would be like what is consciousness is

Voice 2: it something that's

Voice 2: programmed into us is it something that

Voice 2: can be expanded on is it something

Voice 2: that's interdimensional

Voice 1: Those are all good questions.

Voice 1: But I can actually, I can't really

Voice 1: hear you.

Voice 1: Maybe you should cuff up, cough a

Voice 1: little bit or something so I can

Voice 1: hear your voice better.

Voice 2: Sorry.

Voice 1: Yeah, I think that's better.

Voice 1: Can you talk again?

Voice 2: Yeah, sure,

Voice 1: Yeah, yeah, that's much clearer.

Voice 1: Okay, so what were you saying?

Voice 2: I would ask I would like start off

Voice 2: with

Voice 2: two plus two questions and then like

Voice 1: Oh

Voice 1: Like whether it can emergently through

Voice 2: yeah

Voice 1: learning all this audio be able to

Voice 1: count

Voice 1: Do you think it'd be able to

Voice 1: do that?

Voice 2: Oh yeah, for sure.

THE RECORDING
2:56source duration
02assumed voice clusters
87detected speech spans
Source: Block’s Dessa / linked X recording ↗
01 / FOLLOW THE EXCHANGE

A request you can hear.
A change you can inspect.

A request to improve audibility creates a useful question: does the recording get louder afterward? Start with the sound, then inspect the selected windows.

These windows come from a mixed recording. Gain, speech content, and speaker attribution affect the comparison. This is not a pass/fail verdict on Dessa.

WINDOW INSPECTOR2:02—2:04

Establish a reference

A short speech window before the request. This anchors the first comparison.

−19.1 dBFSActive-frame RMS · reference window
16 kHz mono · 20 ms frames · fixed −40 dBFS activity gate
Listen on Block’s page

Open “Talking about the release” and seek to about 2:02. Its timeline starts approximately 0.55 s earlier than the X recording analyzed here.

KEEP THE ORIGINAL IN VIEW

Listen at the source.

The analyzed recording was shared on X. Block’s release page publishes the corresponding conversation and synchronized speaker tracks.

X media metadata credits @blueemi99 as the original publisher. QualityMax is not affiliated with or endorsed by Block or Dessa.

Explore the original release

Hear the recording above, or visit the publisher and the original X post for context.

See Block’s Dessa release ↗Open the original X post ↗
02 / INSPECT THE TIMING

Who speaks. When.

Two anonymous voice clusters, plus uncertain spans. Select a segment to hear it and follow its timing. Speaker numbers are model labels, not verified identities.

Speaker 1 Speaker 2 Uncertain
MODEL ESTIMATES
0:000:441:282:122:56
2:02
SELECTED SPEECH SPANSpeaker 1—

Select a span above to inspect the model’s assignment.

Download analysis JSON

This explorer shows precomputed analysis. Playback uses the original mixed recording; selecting a voice span does not isolate that voice. This page does not transcribe audio, identify people, or run the Dessa model.

03 / KNOW THE LIMITS

Evidence you can question.

One recording can support specific observations. Broader claims need repeatable tests, known speaker labels, and access to a live system.

MEASURED

Audio level & timing

Signal-level changes in selected recording windows. Speech boundaries and anonymous voice groups estimated with Silero VAD and WeSpeaker embeddings.

NEEDS HUMAN REVIEW

Meaning & expression

Whether the response fits the request, a cough is audible, or the conversation resumes appropriately. We have not assigned automated verdicts.

NOT TESTED

Live behavior

Live response latency, interruption handling, reliability across conversations, and human-versus-AI identity are outside this recording analysis.

Reference comparison, exact windows & reproducibility

A narrow reference check

The original model labels agree with activity on Block’s isolated reference tracks for 96.3% of 89.28 seconds of exclusive active reference audio. This is not overall diarization accuracy or a score for Dessa.

Overlapping reference activity (3.22 s) and silent reference frames are excluded. Anonymous IDs are matched by the best permutation. Alignment offset: +0.55475 s; both comparisons use a fixed −40 dBFS gate and 20 ms frames. Overlapping voices are not separated in the analyzed mono recording.

Reproduce the observations

Selected source-recording windows: 122.38–124.00 s, 128.70–137.63 s, and 158.55–168.24 s. The full evidence export includes raw level measurements, span boundaries, model provenance, and source-file hashes.

Window selection is manual. The earlier local experiment used a proposed +3 dB threshold; this public case study reports observations without turning that threshold into an agent-quality verdict.

Download the evidence JSON ↗
QUALITYMAX VOICE LAB

From impressive audio
to inspectable evidence.

An independent research case study exploring how voice behavior could be evaluated. The public page uses precomputed results; it is not a live QualityMax testing feature.

Explore QualityMax