aspeak
App Listed Dormant
A simple text-to-speech client for Azure TTS API.
- Downloads
- 488
- Dependents
- Not applicable
- Stars
- 496
- Forks
- 61
- Contributors
- 7
- Commits
- 632
- Latest release
- 6.1.0 ·
About
:speaking_head: aspeak
A simple text-to-speech client for Azure TTS API. :laughing:
Note
Starting from version 6.0.0, aspeak by default uses the RESTful API of Azure TTS. If you want to use the WebSocket API,
you can specify --mode websocket when invoking aspeak or set mode = "websocket" in the auth section of your profile.
Starting from version 4.0.0, aspeak is rewritten in rust. The old python version is available at the python branch.
You can sign up for an Azure account and then choose a payment plan as needed (or stick to free tier). The free tier includes a quota of 0.5 million characters per month, free of charge.
Please refer to the Authentication section to learn how to set up authentication for aspeak.
Installation
Download from GitHub Releases (Recommended for most users)
Download the latest release from here.
After downloading, extract the archive and you will get a binary executable file.
You can put it in a directory that is in your PATH environment variable so that you can run it from anywhere.
Install from AUR (Recommended for Arch Linux users)
From v4.1.0, You can install aspeak-bin from AUR.
Read the full README
Install from PyPI
Installing from PyPI will also install the python binding of aspeak for you. Check Library Usage#Python for more information on using the python binding.
pip install -U aspeak==6.0.0
Now the prebuilt wheels are only available for x86_64 architecture. Due to some technical issues, I haven't uploaded the source distribution to PyPI yet. So to build wheel from source, you need to follow the instructions in Install from Source.
Because of manylinux compatibility issues, the wheels for linux are not available on PyPI. (But you can still build them from source.)
Install from Source
CLI Only
The easiest way to install aspeak from source is to use cargo:
cargo install aspeak -F binary
Alternatively, you can also install aspeak from AUR.
Python Wheel
To build the python wheel, you need to install maturin first:
pip install maturin
After cloning the repository and cd into the directory
, you can build the wheel by running:
maturin build --release --strip -F python --bindings pyo3 --interpreter python --manifest-path Cargo.toml --out dist-pyo3
maturin build --release --strip --bindings bin -F binary --interpreter python --manifest-path Cargo.toml --out dist-bin
bash merge-wheel.bash
If everything goes well, you will get a wheel file in the dist directory.
Usage
Run aspeak help to see the help message.
Run aspeak help <subcommand> to see the help message of a subcommand.
Authentication
The authentication options should be placed before any subcommand.
For example, to utilize your subscription key and an official endpoint designated by a region, run the following command:
$ aspeak --region <YOUR_REGION> --key <YOUR_SUBSCRIPTION_KEY> text "Hello World"
If you are using a custom endpoint, you can use the --endpoint option instead of --region.
To avoid repetition, you can store your authentication details in your aspeak profile. Read the following section for more details.
From v5.2.0, you can also set the authentication secrets via the following environment variables:
ASPEAK_AUTH_KEYfor authentication using subscription keyASPEAK_AUTH_TOKENfor authentication using authorization token
From v4.3.0, you can let aspeak use a proxy server to connect to the endpoint. For now, only http and socks5 proxies are supported (no https support yet). For example:
$ aspeak --proxy http://your_proxy_server:port text "Hello World"
$ aspeak --proxy socks5://your_proxy_server:port text "Hello World"
aspeak also respects the HTTP_PROXY(or http_proxy) environment variable.
Configuration
aspeak v4 introduces the concept of profiles. A profile is a configuration file where you can specify default values for the command line options.
Run the following command to create your default profile:
$ aspeak config init
To edit the profile, run:
$ aspeak config edit
If you have trouble running the above command, you can edit the profile manually:
Fist get the path of the profile by running:
$ aspeak config where
Then edit the file with your favorite text editor.
The profile is a TOML file. The default profile looks like this:
Check the comments in the config file for more information about available options.
# Profile for aspeak
# GitHub: https://github.com/kxxt/aspeak
# Output verbosity
# 0 - Default
# 1 - Verbose
# The following output verbosity levels are only supported on debug build
# 2 - Debug
# >=3 - Trace
verbosity = 0
#
# Authentication configuration
#
[auth]
# Endpoint for TTS
# endpoint = "wss://eastus.tts.speech.microsoft.com/cognitiveservices/websocket/v1"
# Alternatively, you can specify the region if you are using official endpoints
# region = "eastus"
# Synthesizer Mode, "rest" or "websocket"
# mode = "rest"
# Azure Subscription Key
# key = "YOUR_KEY"
# Authentication Token
# token = "Your Authentication Token"
# Extra http headers (for experts)
# headers = [["X-My-Header", "My-Value"], ["X-My-Header2", "My-Value2"]]
# Proxy
# proxy = "socks5://127.0.0.1:7890"
# Voice list API url
# voice_list_api = "Custom voice list API url"
#
# Configuration for text subcommand
#
[text]
# Voice to use. Note that it takes precedence over the locale
# voice = "en-US-JennyNeural"
# Locale to use
locale = "en-US"
# Rate
# rate = 0
# Pitch
# pitch = 0
# Role
# role = "Boy"
# Style, "general" by default
# style = "general"
# Style degree, a floating-point number between 0.1 and 2.0
# style_degree = 1.0
#
# Output Configuration
#
[output]
# Container Format, Only wav/mp3/ogg/webm is supported.
container = "wav"
# Audio Quality. Run `aspeak list-qualities` to see available qualities.
#
# If you choose a container format that does not support the quality level you specified here,
# we will automatically select the closest level for you.
quality = 0
# Audio Format(for experts). Run `aspeak list-formats` to see available formats.
# Note that it takes precedence over container and quality!
# format = "audio-16khz-128kbitrate-mono-mp3"
If you want to use a profile other than your default profile, you can use the --profile argument:
aspeak --profile <PATH_TO_A_PROFILE> text "Hello"
If you want to temporarily disable the profile, you can use the --no-profile argument:
aspeak --no-profile --region eastus --key <YOUR_KEY> text "Hello"
Pitch and Rate
rate: The speaking rate of the voice.- If you use a float value (say
0.5), the value will be multiplied by 100% and become50.00%. - You can use the following values as well:
x-slow,slow,medium,fast,x-fast,default. - You can also use percentage values directly:
+10%. - You can also use a relative float value (with
fpostfix),1.2f:- According to the Azure documentation,
- A relative value, expressed as a number that acts as a multiplier of the default.
- For example, a value of
1fresults in no change in the rate. A value of0.5fresults in a halving of the rate. A value of3fresults in a tripling of the rate.
- If you use a float value (say
pitch: The pitch of the voice.- If you use a float value (say
-0.5), the value will be multiplied by 100% and become-50.00%. - You can also use the following values as well:
x-low,low,medium,high,x-high,default. - You can also use percentage values directly:
+10%. - You can also use a relative value, (e.g.
-2stor+80Hz):- According to the Azure documentation,
- A relative value, expressed as a number preceded by "+" or "-" and followed by "Hz" or "st" that specifies an amount to change the pitch.
- The "st" indicates the change unit is semitone, which is half of a tone (a half step) on the standard diatonic scale.
- You can also use an absolute value: e.g.
600Hz
- If you use a float value (say
Note: Unreasonable high/low values will be clipped to reasonable values by Azure Cognitive Services.
Examples
The following examples assume that you have already set up authentication in your profile.
Speak "Hello, world!" to default speaker.
$ aspeak text "Hello, world"
SSML to Speech
$ aspeak ssml << EOF
<speak version='1.0' xmlns='http://www.w3.org/2001/10/synthesis' xml:lang='en-US'><voice name='en-US-JennyNeural'>Hello, world!</voice></speak>
EOF
List all available voices.
$ aspeak list-voices
List all available voices for Chinese.
$ aspeak list-voices -l zh-CN
Get information about a voice.
$ aspeak list-voices -v en-US-SaraNeural
Output
Microsoft Server Speech Text to Speech Voice (en-US, SaraNeural)
Display name: Sara
Local name: Sara @ en-US
Locale: English (United States)
Gender: Female
ID: en-US-SaraNeural
Voice type: Neural
Status: GA
Sample rate: 48000Hz
Words per minute: 157
Styles: ["angry", "cheerful", "excited", "friendly", "hopeful", "sad", "shouting", "terrified", "unfriendly", "whispering"]
Save synthesized speech to a file.
$ aspeak text "Hello, world" -o output.wav
If you prefer mp3/ogg/webm, you can use -c mp3/-c ogg/-c webm option.
$ aspeak text "Hello, world" -o output.mp3 -c mp3
$ aspeak text "Hello, world" -o output.ogg -c ogg
$ aspeak text "Hello, world" -o output.webm -c webm
List available quality levels
$ aspeak list-qualities
Output
Qualities for MP3:
3: audio-48khz-192kbitrate-mono-mp3
2: audio-48khz-96kbitrate-mono-mp3
-3: audio-16khz-64kbitrate-mono-mp3
1: audio-24khz-160kbitrate-mono-mp3
-2: audio-16khz-128kbitrate-mono-mp3
-4: audio-16khz-32kbitrate-mono-mp3
-1: audio-24khz-48kbitrate-mono-mp3
0: audio-24khz-96kbitrate-mono-mp3
Qualities for WAV:
-2: riff-8khz-16bit-mono-pcm
1: riff-24khz-16bit-mono-pcm
0: riff-24khz-16bit-mono-pcm
-1: riff-16khz-16bit-mono-pcm
Qualities for OGG:
0: ogg-24khz-16bit-mono-opus
-1: ogg-16khz-16bit-mono-opus
1: ogg-48khz-16bit-mono-opus
Qualities for WEBM:
0: webm-24khz-16bit-mono-opus
-1: webm-16khz-16bit-mono-opus
1: webm-24khz-16bit-24kbps-mono-opus
List available audio formats (For expert users)
$ aspeak list-formats
Output
amr-wb-16000hz
audio-16khz-128kbitrate-mono-mp3
audio-16khz-16bit-32kbps-mono-opus
audio-16khz-32kbitrate-mono-mp3
audio-16khz-64kbitrate-mono-mp3
audio-24khz-160kbitrate-mono-mp3
audio-24khz-16bit-24kbps-mono-opus
audio-24khz-16bit-48kbps-mono-opus
audio-24khz-48kbitrate-mono-mp3
audio-24khz-96kbitrate-mono-mp3
audio-48khz-192kbitrate-mono-mp3
audio-48khz-96kbitrate-mono-mp3
ogg-16khz-16bit-mono-opus
ogg-24khz-16bit-mono-opus
ogg-48khz-16bit-mono-opus
raw-16khz-16bit-mono-pcm
raw-16khz-16bit-mono-truesilk
raw-22050hz-16bit-mono-pcm
raw-24khz-16bit-mono-pcm
raw-24khz-16bit-mono-truesilk
raw-44100hz-16bit-mono-pcm
raw-48khz-16bit-mono-pcm
raw-8khz-16bit-mono-pcm
raw-8khz-8bit-mono-alaw
raw-8khz-8bit-mono-mulaw
riff-16khz-16bit-mono-pcm
riff-22050hz-16bit-mono-pcm
riff-24khz-16bit-mono-pcm
riff-44100hz-16bit-mono-pcm
riff-48khz-16bit-mono-pcm
riff-8khz-16bit-mono-pcm
riff-8khz-8bit-mono-alaw
riff-8khz-8bit-mono-mulaw
webm-16khz-16bit-mono-opus
webm-24khz-16bit-24kbps-mono-opus
webm-24khz-16bit-mono-opus
Increase/Decrease audio qualities
# Less than default quality.
$ aspeak text "Hello, world" -o output.mp3 -c mp3 -q=-1
# Best quality for mp3
$ aspeak text "Hello, world" -o output.mp3 -c mp3 -q=3
Read text from file and speak it.
$ cat input.txt | aspeak text
or
$ aspeak text -f input.txt
with custom encoding:
$ aspeak text -f input.txt -e gbk
Read from stdin and speak it.
$ aspeak text
maybe you prefer:
$ aspeak text -l zh-CN << EOF
我能吞下玻璃而不伤身体。
EOF
Speak Chinese.
$ aspeak text "你好,世界!" -l zh-CN
Use a custom voice.
$ aspeak text "你好,世界!" -v zh-CN-YunjianNeural
Custom pitch, rate and style
$ aspeak text "你好,世界!" -v zh-CN-XiaoxiaoNeural -p 1.5 -r 0.5 -S sad
$ aspeak text "你好,世界!" -v zh-CN-XiaoxiaoNeural -p=-10% -r=+5% -S cheerful
$ aspeak text "你好,世界!" -v zh-CN-XiaoxiaoNeural -p=+40Hz -r=1.2f -S fearful
$ aspeak text "你好,世界!" -v zh-CN-XiaoxiaoNeural -p=high -r=x-slow -S calm
$ aspeak text "你好,世界!" -v zh-CN-XiaoxiaoNeural -p=+1st -r=-7% -S lyrical
Advanced Usage
Use a custom audio format for output
Note: Some audio formats are not supported when outputting to speaker.
$ aspeak text "Hello World" -F riff-48khz-16bit-mono-pcm -o high-quality.wav
Library Usage
Python
The new version of aspeak is written in Rust, and the Python binding is provided by PyO3.
Here is a simple example:
from aspeak import SpeechService
service = SpeechService(region="eastus", key="YOUR_AZURE_SUBSCRIPTION_KEY")
service.speak_text("Hello, world")
First you need to create a SpeechService instance.
When creating a SpeechService instance, you can specify the following parameters:
audio_format(Positional argument): The audio format of the output audio. Default isAudioFormat.Riff24KHz16BitMonoPcm.- You can get an audio format by providing a container format and a quality level:
AudioFormat("mp3", 2).
- You can get an audio format by providing a container format and a quality level:
endpoint: The endpoint of the speech service.region: Alternatively, you can specify the region of the speech service instead of typing the boring endpoint url.key: The subscription key of the speech service.token: The auth token for the speech service. If you provide a token, the subscription key will be ignored.headers: Additional HTTP headers for the speech service.mode: Choose the synthesizer to use. Eitherrestorwebsocket.- In websocket mode, the synthesizer will connect to the endpoint when the
SpeechServiceinstance is created.
- In websocket mode, the synthesizer will connect to the endpoint when the
After that, you can call speak_text() to speak the text or speak_ssml() to speak the SSML.
Or you can call synthesize_text() or synthesize_ssml() to get the audio data.
For synthesize_text() and synthesize_ssml(), if you provide an output, the audio data will be written to that file and the function will return None. Otherwise, the function will return the audio data.
Here are the common options for speak_text() and synthesize_text():
locale: The locale of the voice. Default isen-US.voice: The voice name. Default isen-US-JennyNeural.rate: The speaking rate of the voice. It must be a string that fits the requirements as documented in this section: Pitch and Ratepitch: The pitch of the voice. It must be a string that fits the requirements as documented in this section: Pitch and Ratestyle: The style of the voice.- You can get a list of available styles for a specific voice by executing
aspeak -L -v <VOICE_ID> - The default value is
general.
- You can get a list of available styles for a specific voice by executing
style_degree: The degree of the style.- According to the Azure documentation , style degree specifies the intensity of the speaking style. It is a floating point number between 0.01 and 2, inclusive.
- At the time of writing, style degree adjustments are supported for Chinese (Mandarin, Simplified) neural voices.
role: The role of the voice.- According to the
Azure documentation
,
rolespecifies the speaking role-play. The voice acts as a different age and gender, but the voice name isn't changed. - At the time of writing, role adjustments are supported for these Chinese (Mandarin, Simplified) neural voices:
zh-CN-XiaomoNeural,zh-CN-XiaoxuanNeural,zh-CN-YunxiNeural, andzh-CN-YunyeNeural.
- According to the
Azure documentation
,
Rust
Add aspeak to your Cargo.toml:
$ cargo add aspeak
Then follow the documentation of aspeak crate.
There are 4 examples for quick reference:
Compatibility
- Runs on
- GPU support unknown
What shows it
- no dependency or feature matches a backend row
- Native code
- None found
- No native code found
- Python bindings
- Has Python bindings
- aspeak needs Python only with feature python
- License
- MIT
Compare with similar projects
Order: strongest tier first, then most downloads, then name, with unmeasured values last. A library counts downloads over 30 days. An app counts binary downloads per release. An app with none counts its crate downloads over 30 days. ML Rust runs this catalogue, so its closest project always gets a row.
| Project | Downloads | Dependents | Stars | Latest release | Runs on (GPU) | Native code | License |
|---|---|---|---|---|---|---|---|
|
A simple text-to-speech client for Azure TTS API. Python bindings |
488 binary downloads per release | Not applicable | 496 | 6.1.0 | GPU support unknown | No native code found | MIT |
|
tts-rs Listed
High-level Text-To-Speech (TTS) interface |
21,892 downloads over 30 days | 19 | 143 | 0.26.3 | GPU support unknown | Binds native code: speech-dispatcher-sys, tolk-sys (feature tolk) | MIT |
|
jpreprocess Listed
Japanese text preprocessor for Text-to-Speech application (OpenJTalk rewrite in rust language). |
14,491 downloads over 30 days | 7 | 61 | 0.15.0 | GPU support unknown | No native code found | BSD-3-Clause |
|
msedge-tts Listed
This library is a wrapper of MSEdge Read aloud function API. You can use it to synthesize text to speech with many voices MS provided. |
5,349 downloads over 30 days | 3 | 27 | 0.4.1 | GPU support unknown | No native code found | Apache-2.0 OR MIT |
|
A Rust implementation of the Qwen3 Text-to-Speech (TTS) model inference. |
204 binary downloads per release | Not applicable | 237 | Not measured | Not measured | None stated | |
|
cohere-transcribe-rs Listed
Rust implementation for the CohereLabs/cohere-transcribe-03-2026 speech-to-text model. Includes a CLI and an OpenAI-compatible API server. |
0 downloads over 30 days | 0 | 101 | 0.1.1 | CUDA | Binds native code: torch-sys (feature tch-backend). Build uses a native toolchain: cmake | Apache-2.0 |
|
voxr New
Audio and speech on boostr: compressed-audio decode, resampling, DSP and grapheme to phoneme, with speech synthesis (Kokoro, VITS), voice cloning (VoxCPM2), transcription with word timings (Whisper), voice activity (Silero) and audio-text scoring (CLAP), on CPU or CUDA. |
642 downloads over 30 days | 2 | 2 | 0.9.1 | CUDA | No native code found | Apache-2.0 |
Why ListedNo archive, New or Featured rule places it, so it is Listed.
What it lacks for Featured
- The project is dormant and not finished. Dormancy rule
What else the check found
- The last activity is on 28 Mar 2025, 591 days ago. That reaches the 365 days the rules expect, so the project is dormant. Dormancy rule
- The oldest outside issue waits 469 days for a reply, past the limit of 270. No maintainer replied in 365 days. Rot signals rule
Not measured: Unpatched vulnerabilities past the grace window.
Exact rules: Listed, Featured app. The check on applied thresholds version 9.
Every rule outcome, as the check records it
expected-interval: app: E = 365 daysdormancy: last activity 2025-03-28, 591 days ago, E = 365: dormantrot: oldest unanswered issue 469 days (limit 270), no maintainer reply in 365 daysfeatured: not featured: dormant and not stablelisted: listed: no archive, new or featured rule applies
Measurements and sources
Each signal row shows the raw value, its source and the fetch date. The Sources list gathers every distinct source on this page. Movement needs more history.
Sources6 sources
- Description: the crates.io description
- crates.io database dump, fetched
- GitHub releases, fetched
- GitHub repository, fetched
- crates.io package, fetched
- GitHub contributors, fetched
Adoption488 binary downloads per release4 not measured
| Signal | Value | Source | Fetched | Counts |
|---|---|---|---|---|
| Active dependents | Not measured | Yes | ||
| New dependents (365 days) | Not measured | Yes | ||
| Peak active dependents | Not measured | Yes | ||
| Active dependents as a share of the peak | Not measured | Yes | ||
| Binary downloads per release | 488 | GitHub releases | Yes |
MaintenanceLatest human commit: 19 months ago4 not measured
| Signal | Value | Source | Fetched | Counts |
|---|---|---|---|---|
| Latest human commit | 2025-03-28 | GitHub repository | Yes | |
| Latest release | 2025-03-28 | GitHub releases | Yes | |
| First release | 2023-02-04 | crates.io database dump | Yes | |
| Latest version | 6.1.0 | crates.io database dump | No | |
| Days the oldest outside issue waits for a reply | 469 | GitHub repository | Yes | |
| Maintainer replies over 365 days | 0 | GitHub repository | Yes | |
| Repository archived | false | GitHub repository | Yes | |
| Repository gone | false | GitHub repository | Yes | |
| Release commit or manifest in the repo | true | crates.io package | No | |
| Published docs | Not measured | Yes | ||
| Latest release fails cargo check | Not measured | Yes | ||
| Build check date | Not measured | Yes | ||
| Build check toolchain | Not measured | Yes |
SecurityNot measured
| Signal | Value | Source | Fetched | Counts |
|---|---|---|---|---|
| Unpatched vulnerabilities past the grace window | Not measured | Yes | ||
| RustSec unmaintained advisory | Not measured | Yes | ||
| Deprecation notice | Not measured | Yes | ||
| Deprecated requirement | Not measured | Yes |
Distribution30 releases, 33 downloads over 30 days6 not measured
| Signal | Value | Source | Fetched | Counts |
|---|---|---|---|---|
| Releases | 30 | crates.io database dump | No | |
| Downloads over 30 days | 33 | crates.io database dump | No | |
| Binary downloads over the last 3 releases | 1464 | GitHub releases | Yes | |
| Homebrew installs on request over 365 days | Not measured | Yes | ||
| Repology repository families | Not measured | Yes | ||
| Docker pull growth over 90 days | Not measured | Yes | ||
| Docker pulls at the growth baseline | Not measured | Yes | ||
| Every version a prerelease | false | crates.io database dump | Yes | |
| Every version 0.0.x | false | crates.io database dump | Yes | |
| Every version yanked | Not measured | Yes | ||
| Crate deleted from crates.io | Not measured | Yes |
Repository496 stars, 61 forks, 7 contributors, 632 commits. Stars alone never qualify a project.
| Signal | Value | Source | Fetched | Counts |
|---|---|---|---|---|
| GitHub stars | 496 | GitHub repository | Yes — one part of the repository route | |
| GitHub forks | 61 | GitHub repository | Yes — one part of the repository route | |
| Contributors with a GitHub account | 7 | GitHub contributors | Yes — one part of the repository route | |
| Commits on the default branch | 632 | GitHub repository | No | |
| Repository's main crate left out of the entry | none | crates.io database dump | Yes |
Facts that never count
| Signal | Value | Source | Fetched | Counts |
|---|---|---|---|---|
| License | MIT | crates.io database dump | No | |
| Runs on, from listed crates and their direct dependencies | GPU support unknown | crates.io database dump | No | |
| What shows each backend | no dependency or feature matches a backend row | crates.io database dump | No | |
| Native code, from listed crates and their dependencies | No native code found | crates.io database dump | No | |
| Python bindings, from direct dependencies of listed crates | Has Python bindings: aspeak needs Python only with feature python | crates.io database dump | No | |
| Crates that depend on a listed crate directly | Not measured | No |
Corrections and review history
No correction applies to this entry.
Judgments
A judgment enters only through an approved issue and a merged pull request.
No judgment applies to this entry.