r/TextToSpeech

What do you think are the biggest unsolved challenges in Voice AI that almost nobody is seriously working on right now?

Not “better ASR” or “lower latency” but deeper problems that could define the next generation of voice products/research.

Examples:
- Real-time conversational memory that actually feels human
- Emotion + intent understanding beyond sentiment analysis
- Interruptions/turn-taking that feel natural
- Voice-native UX instead of “ChatGPT but spoken”
- Long-term personalization without being creepy
- Multilingual/code-switching conversations
- Continuous ambient agents
- Social/companion dynamics
- Voice AI for kids/elderly/accessibility
- Real-time multimodal understanding (voice + environment + context)

Curious what people building/using Voice AI think is still fundamentally broken or missing.

I’ve tried a few emotional TTS tools recently (including Noiz.ai and others).

What I notice is:

they often sound great in short sentences, but once you move into longer narration, the tone becomes less consistent.

It feels like we’re still missing a “director layer” for AI voice control.

Is this just a limitation of current models, or are there tools that actually handle long-form emotional consistency well?

What’s a TTS I can run on an apu? I can’t get anything to run. Tia

Google just announced that Elevenlabs will support Google’s SynthID. Do you think this is good for use in YT as voice over? How does it compare with Google’s TTS solution? I’m worried of using TTS if eventually YT will rule against it in the future and my videos get demonetized.

I’ve been using a few AI voice tools recently for short-form storytelling content (TikTok / YouTube Shorts).

Noiz.ai stood out because it actually adds emotional tone, which most TTS tools don’t really do well.

But I’m running into a problem:

sometimes the same script comes out very different emotionally depending on the generation.

One time it sounds perfect, another time it feels over-dramatic or slightly off in pacing.

Curious if others here have found a way to control emotional consistency better in AI voices?

I'm starting with YT automation recently and I need a solid not robotic sounding voice
No voice cloning needed

[Disclaimer: i am totally avoiding fish audio s2 pro because its not a real open-sourced model(non commercial license)]

So the context is i asked many ai to give me best tts model as of now but most of it said qwen 3 tts, and voxtral etc. Nearly none of it ever spoke about LongCat tts and some spoke about Moss tts smaller versions but not the main 8b version.

And the stupid LongCat team didnt even added the text to speech tag in their hugging face repo so its hard to discover.

I am writing this because these both models are heavily underrated for no reason 😑

the #1 longcat Dit 3.5b and #2 Moss tts 8b

Here are the sample by both models by voice cloning. (Real voice also provided) --> https://github.com/9r4n4y/Voice-samples

If you wanna test right now then

For LongCat - https://huggingface.co/spaces/hysts/LongCat-AudioDiT-3.5B

For moss tts - https://studio.mosi.cn/

I’m currently mapping out a long-form audio project (roughly 20–30 hours of total runtime), and I am hitting a massive wall trying to figure out the actual ROI of different paid TTS platforms.

ElevenLabs has amazing quality — probably still the most natural voices overall, but for high-volume, long-form content, it is just completely cost-prohibitive for me right now. I don't need a million ultra-premium cinematic emotional whispers; I just need solid, natural-sounding, highly consistent narration that won't require 15 re-generations (which burns through quotas like crazy).

I’ve been doing some deep dives and found that:

• The Character-to-Hour Conversion Trap: A lot of platforms price at "$X per 1M characters." On paper, 1 million characters sounds like an encyclopedia. In reality, that’s only about 11 to 14 hours of generated audio depending on pacing.
• The Re-generation Tax: If a budget tool sounds robotic 30% of the time, and I have to re-generate paragraphs to fix the glitchy/distorted artifacts, a "generous" monthly quota suddenly gets cut in half.
• API vs. Dashboard Pricing: I noticed OpenAI’s TTS standard API runs around $15 per 1M characters (roughly $1.15 to $1.30 per hour of audio), and their new GPT-4o-mini audio output is dirt cheap at around $0.015 per minute, but the workflow is clunky for a non-coder like me who just wants to paste a script.
• Front-End Apps: I've seen folks mention tools like Podcastle AI (allegedly much cheaper than ElevenLabs for long-form), and Audiobookify (no-subscription models), but I'm wary of hidden limits or sudden voice drop-offs during long scripts.

My Question: If your main metric is strictly Most audio hours generated per dollar spent, what paid platform or wrapper are you actually happy to subscribe to?

Would love to hear from anyone running high-volume channels or doing audiobook narration. Which platform felt affordable at first… until real production work started?

so i tried the Sherpa Korean model, and the quality is very low. Does anyone know about maybe a custom ONNX model for Korean?, i need it to be ONNX because I'm working on a project that requires it to run on a standard mobile phone where resources are rather limited.

Lazypy.ro is basically dead, Cepstral is broken and VoiceForge forces you to pay, is there a site or app that has duplicates of those voices for free?

Hi all,

I've sent emails to the google ai studio feedback team but they have not answered me back. Am I the only one that have problems with the text to speech function?

It used to work like a charm but for the last 10 days it does not. The same prompts and workflow that previously generated good audio now either fail, produce no usable output, or behave differently than before.

Hi, I’m a student who has both adhd and dyslexia. This makes it incredibly difficult for me to read long texts as I bore easily and the fact it’s a challenge to read doesn’t make it any better. So when I found myself needing to read a 55 page article for a class, I sadly started procrastinating. For my brain it is an impossible challenge to read that much text in now two days. So I’m searching for a good tts website. However I am very much against generative ai. I understand that tts algorithms need ai to function but it would be great to grind a non LLM website. I do not want to destroy the climate for my education. And yes I do not have a lot of knowledge about ai. Most of what I know is from friends, family or TikTok. If you don’t have any issue with generative AI please do not interact with this post. I have my personal opinion on generative AI and will not interact with it. If you are also against generative AI and know of a non LLM tts please let me know.

im not very good with using python and a lot seem to need you to use python to download them

As I commute long hours on a daily basis, I would like to stay informed about what is happening with Reddit however, I am unable to read while driving. Perhaps Reddit could provide an audio option to read the updates while driving, which I believe could significantly increase the DAU metric.

I'm running Llama.cpp in OpenWebUI, and have installed Chatterbox TTS to handle the voice side of it, because I really wanted to use a cloned voice locally. I've been at this for hours, trying OpenedAI for TTS, and now Chatterbox. I'm relatively new to Linux and python, etc.

Here's what I've got working:

OpenWebUI sees and uses the model running on Llama.cpp.

Chatterbox Frontend works as expected. Type text, click button, get output in cloned voice. It's a little slow,but that's likely because it's not using my rx580 for inference. Old card, I know.

Here's what looks sketchy to me:

putting in the address for the backend in the browser reveals a terminal like window that simply says: detail: "Not Found".

The actual error:

When trying to generate the TTS part in OpenWebUI, It claims the voice I've very clearly pointed to according to everything I've found, doesn't exist, then proceeds to tell me to use one of the included voices.

What I'm running (old hardware, I know):

AMD Ryzen 5 2600
32GB RAM
RX 580 8G VRAM
OS: Ubuntu 26.04 LTS

Im.using qwen tts and i create my own voice models. Next i used the audio.to clone and narrate text..

The only problem. Cant get emotions in a cloned voice with qwen tts.

I need to add emotions to my cloned voice, and then , use then independant in qwen tts.. (Python coding)

What software should i use to add an emotion to my cloned voice and have a .wav export for that emotion?

My plan is to get sbout 10 emotions for my cloned voice..... And use then as cloned voice in qwentts.....

UPDATE

I’ve already given up on “cloning + emotions”—not even Fish Audio has managed to do it right. (I just need to try Elevenlabs.)

I'm using the “Spanish” language.

I've used Qwen TTS and got a beautiful voice that I really like. The problem is that if I “change” the prompt or the seed, the voice changes completely.

That’s why I can’t create a library of similar voices for different moods (at least with Qwen TTS).

I’ve checked out the ZeroVoice repository, and it’s great (too bad it’s only in English).

What do you recommend for designing a voice and adding emotions to it?

Thanks a lot!!