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The goal of text2speech is to harmonize various text-to-speech engines, including Amazon Polly, Coqui TTS, Google Cloud Text-to-Speech API, Microsoft Cognitive Services Text to Speech REST API, and Speechify Text-to-Speech API.
With the exception of Coqui TTS and Speechify, all these engines are accessible as R packages:
aws.polly
is a client for Amazon
PollygoogleLanguageR
is a client to the Google Cloud
Text-to-Speech APIconrad is
a client to the Microsoft
Cognitive Services Text to Speech REST APIYou might notice Coqui TTS doesn’t have its own R package. This is because, at this time, text2speech directly incorporates the functionality of Coqui TTS.
Speechify is called directly through the Speechify Text-to-Speech API.
Create an API key at https://platform.speechify.ai/api-keys and store it in
the SPEECHIFY_API_KEY environment variable (for example in
your .Renviron), or pass it with
tts_auth("speechify", key_or_json_file = "YOUR_KEY").
You can install this package from CRAN or the development version from GitHub with:
# Install from CRAN
install.packages("text2speech")
# or the development version from GitHub
# install.packages("devtools")
devtools::install_github("jhudsl/text2speech")Check for authentication. If not already authenticated, users must individually configure it for each service.
library(text2speech)
# Amazon Polly
tts_auth("amazon")
#> Warning in pollyHTTP(action = "voices", verb = "GET", query = query, ...):
#> Forbidden (HTTP 403).
#> Warning in structure(out[["Voices"]], NextToken = out[["NextToken"]]): Calling 'structure(NULL, *)' is deprecated, as NULL cannot have attributes.
#> Consider 'structure(list(), *)' instead.
#> [1] TRUE
# Coqui TTS
tts_auth("coqui")
#> [1] TRUE
# Google Cloud Text-to-Speech API
tts_auth("google")
#> [1] TRUE
# Microsoft Cognitive Services Text to Speech REST API
tts_auth("microsoft")
#> [1] TRUE
# Speechify Text-to-Speech API
tts_auth("speechify")
#> [1] TRUEList different voice options for each service.
# Amazon Polly
voices_amazon <- tts_amazon_voices()
head(voices_amazon)
#> voice language language_code gender service
#> 1 Zeina Arabic arb Female amazon
#> 2 Zhiyu Chinese Mandarin cmn-CN Female amazon
#> 3 Naja Danish da-DK Female amazon
#> 4 Mads Danish da-DK Male amazon
#> 5 Sofie Danish da-DK Female amazon
#> 6 Ruben Dutch nl-NL Male amazon
# Coqui TTS
voices_coqui <- tts_coqui_voices()
#> Warning in system("tts --list_models", intern = TRUE): running command 'tts
#> --list_models' had status 1
#> ℹ Test out different voices on the CoquiTTS Demo (<https://huggingface.co/spaces/coqui/CoquiTTS>)
head(voices_coqui)
#> # A tibble: 0 × 5
#> # ℹ 5 variables: type <chr>, language <chr>, dataset <chr>, model_name <chr>,
#> # service <chr>
# Google Cloud Text-to-Speech API
voices_google <- tts_google_voices()
head(voices_google)
#> voice language language_code gender service
#> 1 af-ZA-Standard-A <NA> af-ZA FEMALE google
#> 2 am-ET-Standard-A <NA> am-ET FEMALE google
#> 3 am-ET-Standard-B <NA> am-ET MALE google
#> 4 am-ET-Wavenet-A <NA> am-ET FEMALE google
#> 5 am-ET-Wavenet-B <NA> am-ET MALE google
#> 6 ar-XA-Chirp3-HD-Aoede Arabic ar-XA FEMALE google
# Microsoft Cognitive Services Text to Speech REST API
voices_microsoft <- tts_microsoft_voices()
head(voices_microsoft)
#> voice
#> 1 Microsoft Server Speech Text to Speech Voice (af-ZA, AdriNeural)
#> 2 Microsoft Server Speech Text to Speech Voice (af-ZA, WillemNeural)
#> 3 Microsoft Server Speech Text to Speech Voice (am-ET, MekdesNeural)
#> 4 Microsoft Server Speech Text to Speech Voice (am-ET, AmehaNeural)
#> 5 Microsoft Server Speech Text to Speech Voice (ar-AE, FatimaNeural)
#> 6 Microsoft Server Speech Text to Speech Voice (ar-AE, HamdanNeural)
#> language language_code gender service
#> 1 Afrikaans (South Africa) af-ZA Female microsoft
#> 2 Afrikaans (South Africa) af-ZA Male microsoft
#> 3 Amharic (Ethiopia) am-ET Female microsoft
#> 4 Amharic (Ethiopia) am-ET Male microsoft
#> 5 Arabic (United Arab Emirates) ar-AE Female microsoft
#> 6 Arabic (United Arab Emirates) ar-AE Male microsoft# Speechify Text-to-Speech API
voices_speechify <- tts_speechify_voices()
head(voices_speechify)
#> voice language language_code gender service
#> 1 aadi Hindi hi-IN male speechify
#> 2 aaliya Urdu ur-IN female speechify
#> 3 aamir Urdu ur-IN male speechify
#> 4 abhay Hindi hi-IN male speechify
#> 5 abhijit Bengali bn-IN male speechify
#> 6 abirami Tamil ta-IN female speechifySynthesize speech with
tts(text = "TEXT", service = "ENGINE")
# Amazon Polly
tts("Hello world!", service = "amazon")
# Coqui TTS
tts("Hello world!", service = "coqui")
# Google Cloud Text-to-Speech API
tts("Hello world!", service = "google")
# Microsoft Cognitive Services Text to Speech REST API
tts("Hello world!", service = "microsoft")
# Speechify Text-to-Speech API
tts("Hello world!", service = "speechify")The resulting output will consist of a standardized
tibble featuring the following columns:
index: Sequential identifier numberoriginal_text: The text input provided by the usertext: In case original_text exceeds the
character limit, text represents the outcome of splitting
original_text. Otherwise, text remains the
same as original_text.wav: Wave object (S4 class)file: File path to the audio fileaudio_type: The audio format, either mp3 or wavduration : The duration of the audio fileservice: The text-to-speech engine usedThese binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.