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 used