Tech & AIAI FutureI Built a Voice AI Workflow with Fish Audio — Here’s What Actually Worked

I Built a Voice AI Workflow with Fish Audio — Here’s What Actually Worked

Long-form8:10People & BlogsPublished Sep 23, 2026, 3:11 AM · 4w ago
Views
45,571
views/hour after the next reading
Views / hour now
—
needs two readings
Peak views / hour
—
 
First 24 hours
—
not tracked from upload
Engagement
2.1%
likes + comments / views
Likes
732
1.6% of views
Comments
202
0.44% of views
Est. ad revenue
$319–$729
lifetime, $7–16 RPM

Checked every 12 h while the video is this age · last check 7h ago · next in 275 min. YouTube itself updates public counts with a short delay.

Avg views / day
1.6K
since upload
vs channel median
1.0×
this video's views ÷ the channel's usual
Rank in channel
#11
of 20 tracked

Views over time

1 readings

Total views Views gained per hour
Live tracking started
The chart fills in as FameX records new readings.

Description

Sponsored by Fish Audio. In this video, I build a practical Voice AI workflow using Fish Audio S2.1 Pro, exploring expressive text-to-speech, emotion controls, voice cloning, voice design, real-time streaming, and MCP integration for AI agents. You’ll see how Fish Audio can become the voice layer inside avatars, assistants, games, educational tools, and automated content workflows. S2.1 Pro is currently available as a free TTS API under the Fair Use Policy through the end of November. Try the API and MCP tools, build your own experiment, and share your results below with other developers today. https://fish.audio/?fpr=s3lyoi #FishAudio #FishAudioTurns1 #VoiceAI #AITools

Statistics from the YouTube Data API, tracked by FameX. Views per hour, revenue and comparisons are FameX estimates.