Add initial clone of previous space.'

.gitignore

@@ -0,0 +1,167 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/latest/usage/project/#working-with-version-control
+.pdm.toml
+.pdm-python
+.pdm-build/
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+
+
+# MY FILES
+dev_roadmap.txt

README.md

@@ -1,19 +1,24 @@
 ---
-title: Tts Mockingbird V2
-emoji: 🚀
-colorFrom: red
-colorTo: red
-sdk: docker
-app_port: 8501
-tags:
-- streamlit
+title: "Mockingbird"
+app_file: app.py
+sdk: "streamlit"
+python_version: 3.11.8
+streamlit_version: 1.44.1
 pinned: false
-short_description: Streamlit template space
 ---
 
-# Welcome to Streamlit!
+# Mockingbird TTS Demo
+This repo hosts Mockingbird, a demo of open Text-to-Speech tools.
 
-Edit `/src/streamlit_app.py` to customize this app to your heart's desire. :heart:
+Currently, 3 synthesizers are supported:
+- [**Meta's Massively Multilingual Speech (MMS)**](https://ai.meta.com/blog/multilingual-model-speech-recognition/) model
+- [**Coqui's TTS**](https://docs.coqui.ai/en/latest/#) package and the models supplied via that
+- [**ESpeak-NG's**](espeak-ng) synthetic voices
 
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
+Voice conversion is achieved through Coqui.
+
+Notes:
+1. ESpeak-NG seems to have the worst performance out of the box, but it has a lot of options for controlling voice output.
+2. Coqui is no longer being officially developed.
+3. Where a synthesizer supports multiple models/voices, I manually pick the appropriate model.
+4. Not all synthesizers support a given language.

app.py

@@ -0,0 +1,293 @@
+import torch
+import scipy
+import os
+import streamlit as st
+import pandas as pd
+from transformers import pipeline #set_seed, 
+from transformers import VitsTokenizer, VitsModel
+from datasets import load_dataset, Audio
+from huggingface_hub.inference_api import InferenceApi
+
+from src import *
+
+
+########################
+col1,  col2 = st.columns([20,3])
+with col2:
+    st.image('logo.png', use_container_width=True)
+with col1:
+    st.title("Mockingbird")
+st.header("A demo of open Text to Speech tools")
+    
+tts, about = st.tabs(["Text to speech",   "**About**"])
+
+########################
+with tts:
+
+    # Configurations -- language choice and text
+    tts_lang = st.selectbox('Language of text', (language_list), format_func = decode_iso)    
+    tts_text = st.text_area(label = "Please enter your sentence here:", 
+                            value="", placeholder=placeholders[tts_lang] ) 
+            
+    target_speaker_file = st.file_uploader("If you would like to test voice conversion, you may upload your audio below. You should upload one file in .wav format. If you don't, a default file will be used.", 
+type=['wav'])
+
+    # Inference
+    if st.button("Generate"):
+
+        # Warning about alphabet support
+        if tts_lang in ['rus', 'fas']:
+            st.warning("WARNING! On Windows, ESpeak-NG has trouble synthesizing output when input is provided from non-Latin alphabets.")
+            
+        st.divider()
+
+        # Synthesis
+        with st.spinner(":rainbow[Synthesizing, please wait... (this will be slowest the first time you generate audio in a new language)]"):
+            if tts_text == "":
+                tts_text=placeholders[tts_lang]
+
+            # First, make the audio
+            base_mms = synth_mms(tts_text, models[tts_lang]['mms'])
+            base_coqui= synth_coqui(tts_text, models[tts_lang]['coqui'])
+            base_espeakng= synth_espeakng(tts_text, models[tts_lang]['espeakng'])
+            try:
+                base_toucan= synth_toucan(tts_text, models[tts_lang]['toucan'])
+            except:
+                base_toucan=None
+            base_piper= synth_piper(tts_text, models[tts_lang]['piper'])
+
+            if tts_lang=="swh":
+                finetuned_mms1 = synth_mms(tts_text, "khof312/mms-tts-swh-female-1")
+                finetuned_mms2 = synth_mms(tts_text, "khof312/mms-tts-swh-female-2")
+            if tts_lang=="spa":
+                finetuned_mms1 = synth_mms(tts_text, "ylacombe/mms-spa-finetuned-argentinian-monospeaker")
+                finetuned_mms2 = synth_mms(tts_text, "ylacombe/mms-spa-finetuned-chilean-monospeaker")
+                finetuned_mms3 = synth_mms(tts_text, "ylacombe/mms-spa-finetuned-colombian-monospeaker")
+                #finetuned_mms4 = synth_mms(tts_text, "khof312/mms-tts-spa-female")
+            if tts_lang=="lin":
+                #finetuned_mms1 = synth_mms(tts_text, "khof312/mms-tts-lin-female")
+                try:
+                    finetuned_africanvoices = synth_africanvoices(tts_text, models[tts_lang]['africanvoices'])
+                except:
+                    pass
+            
+            #vc_mms
+            #vc_coqui
+            #vc_espeakng
+            "## Synthesis"
+            "### Default models"
+            row1 = st.columns([1,1,2])
+            row2 = st.columns([1,1,2])
+            row3 = st.columns([1,1,2])
+            row4 = st.columns([1,1,2])
+            row5 = st.columns([1,1,2])
+            row6 = st.columns([1,1,2])
+            
+            row1[0].write("**Model**")
+            row1[1].write("**Configuration**")
+            row1[2].write("**Audio**")
+
+            if base_mms is not None:
+                row2[0].write(f"[Meta MMS](https://huggingface.co/docs/transformers/main/en/model_doc/mms)")
+                row2[1].write("default") 
+                row2[2].audio(base_mms[0], sample_rate = base_mms[1]) 
+            
+            if base_coqui is not None:
+                row3[0].write(f"[Coqui](https://docs.coqui.ai/en/latest/index.html)")
+                row3[1].write("default") 
+                row3[2].audio(base_coqui[0], sample_rate = base_coqui[1]) 
+            
+            if base_espeakng is not None:
+                row4[0].write(f"[Espeak-ng](https://github.com/espeak-ng/espeak-ng)")
+                row4[1].write("default") 
+                row4[2].audio(base_espeakng[0], sample_rate = base_espeakng[1]) 
+
+            if base_toucan is not None:
+                row5[0].write(f"[IMS-Toucan](https://github.com/DigitalPhonetics/IMS-Toucan)")
+                row5[1].write("default") 
+                row5[2].audio(base_toucan[0], sample_rate = base_toucan[1]) 
+            
+            if base_piper is not None:
+                row6[0].write(f"[Piper](https://github.com/rhasspy/piper)")
+                row6[1].write("default") 
+                row6[2].audio(base_piper[0], sample_rate = base_piper[1]) 
+                
+            #################################################################
+            if tts_lang == "swh":            
+                "### Fine Tuned" 
+                row1 = st.columns([1,1,2])
+                row2 = st.columns([1,1,2])
+                row3 = st.columns([1,1,2])
+                
+                row1[0].write("**Model**")
+                row1[1].write("**Configuration**")
+                row1[2].write("**Audio**")
+                
+                row2[0].write(f"Meta MMS")
+                row2[1].write("[female 1](https://huggingface.co/khof312/mms-tts-swh-female-1)") 
+                row2[2].audio(finetuned_mms1[0], sample_rate = finetuned_mms1[1]) 
+                row3[0].write(f"Meta MMS")
+                row3[1].write("[female 2](https://huggingface.co/khof312/mms-tts-swh-female-2)") 
+                row3[2].audio(finetuned_mms2[0], sample_rate = finetuned_mms2[1]) 
+
+            
+            if tts_lang == "spa":            
+                "### Fine Tuned" 
+                row1 = st.columns([1,1,2])
+                row2 = st.columns([1,1,2])
+                row3 = st.columns([1,1,2])
+                row4 = st.columns([1,1,2])
+                #row5 = st.columns([1,1,2])
+                
+                row1[0].write("**Model**")
+                row1[1].write("**Configuration**")
+                row1[2].write("**Audio**")
+                
+                row2[0].write(f"Meta MMS")
+                row2[1].write("[ylacombe - Argentinian](https://huggingface.co/ylacombe/mms-spa-finetuned-argentinian-monospeaker)") 
+                row2[2].audio(finetuned_mms1[0], sample_rate = finetuned_mms1[1]) 
+                row3[0].write(f"Meta MMS")
+                row3[1].write("[ylacombe - Chilean](https://huggingface.co/ylacombe/mms-spa-finetuned-chilean-monospeaker)") 
+                row3[2].audio(finetuned_mms2[0], sample_rate = finetuned_mms2[1]) 
+                row4[0].write(f"Meta MMS")
+                row4[1].write("[ylacombe - Colombian](https://huggingface.co/ylacombe/mms-spa-finetuned-colombian-monospeaker)") 
+                row4[2].audio(finetuned_mms3[0], sample_rate = finetuned_mms3[1]) 
+                #row5[0].write(f"Meta MMS")
+                #row5[1].write("[khof312 - female](https://huggingface.co/khof312/mms-tts-spa-female)") 
+                #row5[2].audio(finetuned_mms4[0], sample_rate = finetuned_mms4[1]) 
+                
+            if tts_lang == "lin":            
+                "### Fine Tuned" 
+                row1 = st.columns([1,1,2])
+                #row2 = st.columns([1,1,2])
+                row3 = st.columns([1,1,2])
+                
+                row1[0].write("**Model**")
+                row1[1].write("**Configuration**")
+                row1[2].write("**Audio**")
+                
+                #row2[0].write(f"Meta MMS")
+                #row2[1].write("[khof312 - female](https://huggingface.co/khof312/mms-tts-lin-female)") 
+                #row2[2].audio(finetuned_mms1[0], sample_rate = finetuned_mms1[1]) 
+    
+                try:
+                    row3[0].write(f"African voices")
+                    row3[1].write("[African Voices]()") 
+                    row3[2].audio(finetuned_africanvoices[0], sample_rate = finetuned_africanvoices[1]) 
+                except:
+                    pass
+            
+            st.divider()
+                        
+            "## Voice conversion" #################################################################
+            
+            
+                        
+            st.warning('''Note: The naturalness of the audio will only be as good as that of the audio in "default models" above.''')
+
+            if target_speaker_file is not None:
+                rate, wav = scipy.io.wavfile.read(target_speaker_file)
+                scipy.io.wavfile.write("target_speaker_custom.wav", data=wav, rate=rate)
+                target_speaker = "target_speaker_custom.wav"
+            else:
+                target_speaker = "target_speaker.wav"
+                
+            if base_mms is not None:
+                scipy.io.wavfile.write("source_speaker_mms.wav", rate=base_mms[1], data=base_mms[0].T)
+                converted_mms = convert_coqui('source_speaker_mms.wav', target_speaker)
+
+            if base_coqui is not None:
+                scipy.io.wavfile.write("source_speaker_coqui.wav", rate=base_coqui[1], data=base_coqui[0].T)
+                converted_coqui = convert_coqui('source_speaker_coqui.wav', target_speaker)
+
+            if base_espeakng is not None:
+                scipy.io.wavfile.write("source_speaker_espeakng.wav", rate=base_espeakng[1], data=base_espeakng[0].T)
+                converted_espeakng = convert_coqui('source_speaker_espeakng.wav', target_speaker)
+
+            scipy.io.wavfile.write("source_speaker_toucan.wav", rate=base_toucan[1], data=base_toucan[0].T)
+            converted_toucan = convert_coqui('source_speaker_toucan.wav', target_speaker)
+
+            row1 = st.columns([1,1,2])
+            row2 = st.columns([1,1,2])
+            row3 = st.columns([1,1,2])
+            row4 = st.columns([1,1,2])
+            
+            row1[0].write("**Model**")
+            row1[1].write("**Configuration**")
+            row1[2].write("**Audio**")
+            
+            if base_mms is not None:
+                row1[0].write(f"Meta MMS")
+                row1[1].write(f"converted") 
+                row1[2].audio(converted_mms[0], sample_rate = converted_mms[1]) 
+            
+            if base_coqui is not None:
+                row2[0].write(f"Coqui")
+                row2[1].write(f"converted") 
+                row2[2].audio(converted_coqui[0], sample_rate = converted_coqui[1]) 
+            
+            if base_espeakng is not None:
+                row3[0].write(f"Espeak-ng")
+                row3[1].write(f"converted") 
+                row3[2].audio(converted_espeakng[0], sample_rate = converted_espeakng[1]) 
+
+
+            row4[0].write(f"IMS Toucan")
+            row4[1].write(f"converted") 
+            row4[2].audio(converted_toucan[0], sample_rate = converted_toucan[1]) 
+                        
+    
+                #row3[0].write("MMS-TTS-SWH")
+                #row3[1].audio(synth, sample_rate=16_000)
+                #row3[2].audio(synth, sample_rate=16_000)
+    
+                #st.audio(synth, sample_rate=16_000)
+                #data.write(np.random.randn(10, 1)
+    
+                
+                #col1.subheader("A wide column with a chart")
+                #col1.line_chart(data)
+                
+                #col2.subheader("A narrow column with the data")
+                #col2.write(data)
+
+with about:
+    #st.header("How it works")
+    st.markdown('''# Mockingbird TTS Demo
+This page is a demo of the openly available Text to Speech models for various languages of interest. Currently, 3 synthesizers with multilingual offerings are supported out of the box:
+- [**Meta's Massively Multilingual Speech (MMS)**](https://ai.meta.com/blog/multilingual-model-speech-recognition/) model, which supports over 1000 languages.[^1]
+- [**IMS Toucan**](https://github.com/DigitalPhonetics/IMS-Toucan), which supports 7000 languages.[^4]
+- [**ESpeak-NG's**](https://github.com/espeak-ng/espeak-ng/tree/master)'s synthetic voices**[^3]
+
+On a case-by-case basis, for different languages of interest, I have added:
+- [**Coqui's TTS**](https://docs.coqui.ai/en/latest/#) package;[^2] while no longer supported, Coqui acted as a hub for TTS model hosting and these models are still available. Languages must be added on a model-by-model basis.
+- Specific fine-tuned variants of Meta's MMS (either fine-tuned by [Yoach Lacombe](https://huggingface.co/ylacombe), or fine-tuned by me using his scripts).
+
+I am in the process of adding support for:
+- [**Piper**](https://github.com/rhasspy/piper), a TTS system that supports multiple voices per language and approximately 30 languages. To test different voices, please see the [Huggingface demo](https://huggingface.co/spaces/k2-fsa/text-to-speech).[^5]
+- [**African Voices**](https://github.com/neulab/AfricanVoices), a CMU research project that fine-tuned synthesizers for different African languages. The site hosting the synthesizers is deprecated but they can be downloaded from Google's Wayback Machine. [^6]
+
+
+Voice conversion is currently achieved through Coqui.
+
+Notes:
+1. ESpeak-NG seems to have the worst performance out of the box, but it has a lot of options for controlling voice output.
+2. Where a synthesizer supports multiple models/voices, I manually pick the appropriate model.
+3. Not all synthesizers support a given language.
+
+
+
+[^1]: Endpoints used are of the form https://huggingface.co/facebook/mms-tts-[LANG].
+    Learn more:
+    [Docs](https://huggingface.co/docs/transformers/model_doc/mms) | 
+    [Paper](https://arxiv.org/abs/2305.13516) | 
+    [Supported languages](https://dl.fbaipublicfiles.com/mms/misc/language_coverage_mms.html)
+    
+[^2]: [Available models](https://github.com/coqui-ai/TTS/blob/dev/TTS/.models.json)
+[^3]: [Language list](https://github.com/espeak-ng/espeak-ng/blob/master/docs/languages.md)
+[^4]: Language list is available in the Gradio API documentation [here](https://huggingface.co/spaces/Flux9665/MassivelyMultilingualTTS).
+[^5]: The list of available voices is [here](https://github.com/rhasspy/piper/blob/master/VOICES.md), model checkpoints are [here](https://huggingface.co/datasets/rhasspy/piper-checkpoints/tree/main), and they can be tested [here](https://rhasspy.github.io/piper-samples/).
+[^6]: 
+''')
+
+

packages.txt

@@ -0,0 +1 @@
+espeak-ng

requirements.txt

@@ -1,3 +1,14 @@
-altair
-pandas
-streamlit
+datasets==2.14.7
+librosa==0.10.1
+pycountry==24.6.1
+scipy==1.12.0
+sentencepiece==0.2.0
+transformers>=2.5
+torch
+IPython==8.26.0
+TTS
+pandas==1.5.3
+wave
+#py-espeak-ng
+espeakng
+dotenv

src/__init__.py

@@ -0,0 +1,4 @@
+from .helpers import *
+from .lookups import *
+from .synthesize import *
+from .convert import *

src/convert.py

@@ -0,0 +1,21 @@
+import torch
+import IPython
+from TTS.api import TTS
+
+def convert_coqui(source_wav:str, target_wav:str):    
+    '''
+    Use Coqui TTS for zero-shot voice conversion.
+
+    Inputs:
+        source_wav: Wav of the thing you want to say.
+        target_wav: Wav of the speaker you want to hear.
+    Returns:
+        Streaming wav and sampling rate.
+    '''
+    # Get device
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+    
+    tts = TTS(model_name="voice_conversion_models/multilingual/vctk/freevc24", progress_bar=False).to(device)
+    wav = tts.voice_conversion(source_wav=source_wav, target_wav=target_wav)
+
+    return wav, 24000 # Identified sampling rate of freevc24

src/helpers.py

@@ -0,0 +1,29 @@
+import pycountry
+
+iso_encoder = {"English":"eng",
+       "French":"fra",
+       "Moore": "mos"}
+
+iso_decoder = dict((v,k) for k,v in iso_encoder.items())
+
+
+
+def encode_iso(lang:str)-> str:
+    '''   Takes the name of a language and returns its ISO-3 code.   '''
+    return  iso_encoder[lang]
+
+def decode_iso(iso:str)-> str:
+    '''  Takes an ISO-3 code and returns the name of the language.   '''
+
+    if "-" in iso:
+        iso, suffix = iso.split("-", 1)
+    else:
+        suffix = None
+        
+    name = pycountry.languages.get(alpha_3 = iso).name
+    name = name.replace("Mossi", "Mooré").replace("Swahili (individual language)", "Swahili")
+
+    if suffix is not None:
+        name+= f" - {suffix}"
+    
+    return name

src/lookups.py

@@ -0,0 +1,162 @@
+language_list = ['swh', 'ara','mya', 'eng', 'fra', 'hat', 'kmr', 'lin','mos','fas', 'por','ron', 'run','rus','spa', 'tur', 'ukr', 'urd'
+                 #'ara','fas','ukr','tur', 'mya', 'rus',
+                #'kmr-script_latin', 'urd-script_arabic', 'urd-script_devanagari', 'urd-script_latin',
+                ]
+
+#####################################
+placeholders = {
+    'swh': "Mfuko wa Kimataifa wa Watoto",
+    'ara': "منظمة الأمم المتحدة للطفولة",
+    'eng': "the United Nations International Children's Emergency Fund", 
+    'fra': "Le Fonds des Nations unies pour l'enfance",
+    'hat': "Fon pou Timoun Nasyon Ini yo",
+    'fas': "صندوق کودکان ملل متحد", 
+    'kmr': "سندووقی مناڵانی نەتەوە یەکگرتووەکان",
+    'lin': 'Your phrase here',
+    'mos': 'Your phrase here',
+    'mya': "ကုလသမဂ္ဂ အပြည်ပြည်ဆိုင်ရာ ကလေးများရန်ပုံငွေအဖွဲ့",
+    'por': "O Fundo das Nações Unidas para a Infância",
+    'ron': "Fondul Internațional pentru Urgențe ale Copiilor al Națiunilor Unite",
+    'run': "Your phrase here",
+    'rus': 'Международного фонда помощи детям',
+    'spa': "El Fondo de las Naciones Unidas para la Infancia",
+    'tur': "Birleşmiş Milletler Çocuklara Yardım Fonu",
+    'ukr': "Дитя́чий фонд Організа́ція Об'є́днаних На́цій",
+    'urd': "اقوام متحدہ کا فنڈ برائے اطفال"
+}
+
+#####################################
+models = {
+'swh': {
+    'mms': 'facebook/mms-tts-swh',
+    'coqui': None,
+    'espeakng': 'sw',
+    'toucan': 'Congo Swahili (swc)',
+    'piper': ['Swahili', 'csukuangfj/vits-piper-sw_CD-lanfrica-medium'],
+},
+'ara': {
+    'mms': 'facebook/mms-tts-ara',
+    'coqui': None, ################
+    'espeakng': 'ar',
+    'toucan': 'Standard Arabic (arb)',
+    'piper': ['Arabic','csukuangfj/vits-piper-ar_JO-kareem-low'] # Other variant(s) exist but have been left out
+},
+'mya': {
+    'mms': 'facebook/mms-tts-mya',
+    'coqui': None, ################
+    'espeakng': 'my',
+    'toucan': 'Burmese (mya)',
+    'piper': None
+},      
+'eng': {
+    'mms': 'facebook/mms-tts-eng',
+    'coqui': None,
+    'espeakng': 'en',
+    'toucan': 'English (eng)',
+    'piper': ['English', 'csukuangfj/vits-piper-en_US-glados|1 speaker'] # Other variant(s) exist but have been left out
+},  
+'fas':{
+    'mms': 'facebook/mms-tts-fas',
+    'coqui': None, #'tts_models/fa/custom/glow-tts',
+    'espeakng': 'fa',
+    'toucan': 'Persian (pes)', #'Dari (prs)'
+    'piper': ['Persian', 'csukuangfj/vits-piper-fa_IR-amir-medium'],
+               #['Persian', 'csukuangfj/vits-piper-fa_IR-gyro-medium']],
+    #'mimic3': ['csukuangfj/vits-mimic3-fa-haaniye_low']
+}  , 
+'fra':{
+    'mms': 'facebook/mms-tts-fra',
+    'coqui': 'tts_models/fr/css10/vits', # Sampling rate: 22050  ## k2-fsa: 'csukuangfj/vits-coqui-fr-css10'
+    'espeakng': 'fr',
+    'toucan': 'French (fra)',
+    'piper': ['French', 'csukuangfj/vits-piper-fr_FR-upmc-medium'] # Other variant(s) exist but have been left out
+},
+'hat':{
+    'mms': 'facebook/mms-tts-hat',
+    'coqui': None,
+    'espeakng': 'ht',
+    'toucan': 'Haitian Creole (hat)',
+    'piper': None
+},
+'kmr': {
+    'mms': 'facebook/mms-tts-kmr-script_arabic',
+    'coqui': None, ################
+    'espeakng': 'ku',
+    'toucan': 'Kurdish (ckb)',
+    'piper': None
+},
+'lin':{
+    'mms': None,
+    'coqui': 'tts_models/lin/openbible/vits', # Sampling rate: 22050
+    'espeakng': None,
+    'toucan': 'Lingala (lin)',
+    'piper': None,
+    'africanvoices': 'cmu_lin_ope',
+}, 
+'mos':{
+    'mms': 'facebook/mms-tts-mos',
+    'coqui': None,
+    'espeakng': None,
+    'toucan': 'Mossi (mos)',
+    'piper': None
+}  , 
+    # 'Southern Pashto (pbt)', 'Northern Pashto (pbu)'
+'por':{
+    'mms': 'facebook/mms-tts-por',
+    'coqui': 'tts_models/pt/cv/vits', # Sampling rate: 22050
+    'espeakng': 'pt-br',
+    'toucan': 'Brazilian Portuguese (pt-br)',
+    'piper': ['Portuguese', 'csukuangfj/vits-piper-pt_BR-edresson-low'],
+              #['Portuguese', 'csukuangfj/csukuangfj/vits-piper-pt_BR-faber-medium']
+},
+'ron':{
+    'mms': 'facebook/mms-tts-ron',
+    'coqui': 'tts_models/ro/cv/vits', # Sampling rate: 22050 # csukuangfj/vits-coqui-ro-cv
+    'espeakng': 'ro',
+    'toucan': 'Romanian (ron)',
+    'piper': ['Romanian', 'csukuangfj/vits-piper-ro_RO-mihai-medium']
+}, 
+'run':{
+    'mms': 'facebook/mms-tts-run',
+    'coqui': None,
+    'espeakng': None,
+    'toucan': 'Rundi (run)',
+    'piper': None
+}, 
+'rus':{
+    'mms': 'facebook/mms-tts-rus',
+    'coqui': None,
+    'espeakng': 'ru',
+    'toucan': 'Russian (rus)',
+    'piper': ['Russian', 'csukuangfj/vits-piper-ru_RU-irina-medium'] # Other variant(s) exist but have been left out
+} ,
+'spa':{
+    'mms': 'facebook/mms-tts-spa',
+    'coqui': 'tts_models/es/css10/vits', # Sampling rate: 22050
+    'espeakng': 'es-419',
+    'toucan': 'Spanish (spa)',
+    'piper': ['Spanish', 'csukuangfj/vits-piper-es-glados-medium'] # Other variant(s) exist but have been left out
+},  
+'tur': {
+    'mms': 'facebook/mms-tts-tur',
+    'coqui': None, ################
+    'espeakng': 'tr',
+    'toucan': 'Turkish (tur)',
+    'piper': ['Turkish', 'csukuangfj/vits-piper-tr_TR-dfki-medium'] # Other variant(s) exist but have been left out
+},      
+'ukr': {
+    'mms': 'facebook/mms-tts-ukr',
+    'coqui': None, ################
+    'espeakng': 'uk',
+    'toucan': 'Ukrainian (ukr)',
+    'piper': ['Ukrainian', 'csukuangfj/vits-piper-uk_UA-lada-x_low'] # Other variant(s) exist but have been left out
+},     
+'urd': {
+    'mms': 'facebook/mms-tts-urd-script_arabic',
+    'coqui': None, ################
+    'espeakng': 'ur',
+    'toucan': 'Urdu (urd)',
+    'piper': None
+},        
+}
+

src/synthesize.py

@@ -0,0 +1,174 @@
+import IPython
+from huggingface_hub.inference_api import InferenceApi
+import torch
+from TTS.api import TTS
+import wave
+import espeakng 
+import subprocess
+from scipy.io import wavfile
+from transformers import pipeline
+import os
+import numpy as np
+from gradio_client import Client, handle_file
+
+from dotenv import load_dotenv
+# Load environment variables
+load_dotenv()
+
+
+def synth_mms(text:str, model:str):
+    '''
+    Use Huggingface inference pipeline to synthesize text.
+    (Can be replaced by inference API, but that requires stored API token.)
+
+    Inputs:
+        text: Text to synthesze
+        model: Model code of the form mms-tts-LAN
+    Returns:
+        Streaming numpy and sampling rate.
+    '''
+    #inference = InferenceApi(repo_id=f"facebook/{model}", 
+    #                         token=API_TOKEN)
+    #mms_tts = inference(inputs=text, 
+    #                    raw_response=True)._content
+
+    if model is not None:
+        pipe = pipeline("text-to-speech", model=model, device=-1, token=os.environ['HUGGINGFACE_KEY']
+                       ) # Change device if it should use GPU
+        mms_tts = pipe(text)
+        return mms_tts['audio'], mms_tts['sampling_rate']
+    else:
+        return None
+
+
+
+def synth_coqui(text:str, model:str):
+    '''
+    Use Coqui inference API to synthesize text.
+
+    Inputs:
+        text: Text to synthesze
+        model: Model code 
+    Returns:
+        Streaming Wav and sampling rate. 
+        
+    IMPORTANT: Current implementation assumes 22050 sampling rate, this should be verified when adding a new model.
+    '''
+    if model is not None:
+        # Get device
+        device = "cuda" if torch.cuda.is_available() else "cpu"
+        
+        # Init TTS
+        tts = TTS(model, progress_bar=False).to(device)
+
+        # Infer
+        wav = tts.tts(text=text) # is_multi_speaker=False
+        
+        return np.array(wav), 22050
+    else:
+        return None
+
+
+def synth_espeakng(text:str, model:str):
+    '''
+    Use ESpeak-NG to synthesize text.
+
+    Inputs:
+        text: Text to synthesze
+        model: Model code 
+    Returns:
+        Streaming Wav and sampling rate.
+    '''
+    if model is not None:
+        
+        subprocess.run(['espeak-ng', f'-v{model}', "-w test.wav", text]) 
+        #esng = espeakng.Speaker()
+        #esng.voice = model
+        #esng.say(text, export_path="test.wav")
+
+        sampling_rate, wav = wavfile.read('test.wav')
+        os.remove("test.wav")
+        
+        #wav = tts.tts(text=text)
+        return wav, sampling_rate
+    else:
+        return None
+        
+def synth_africanvoices(text:str, model:str):
+    '''
+    Use ESpeak-NG to synthesize text.
+
+    Inputs:
+        text: Text to synthesze
+        model: Model code 
+    Returns:
+        Streaming Wav and sampling rate.
+    '''
+    if model is not None:
+        
+        subprocess.run(['flite', f'-voice {model}.flitevox', f'"{text}"', " test.wav"]) 
+        #esng = espeakng.Speaker()
+        #esng.voice = model
+        #esng.say(text, export_path="test.wav")
+
+        sampling_rate, wav = wavfile.read('test.wav')
+        os.remove("test.wav")
+        
+        #wav = tts.tts(text=text)
+        return wav, sampling_rate
+    else:
+        return None
+
+def synth_toucan(text:str, model:str):
+    '''
+    Use Toucan to synthesize text.
+
+    Inputs:
+        text: Text to synthesze
+        model: Model code 
+    Returns:
+        Streaming Wav and sampling rate.
+
+    NOTES: (1)This wrapper does not let you explore the full range of options possible with the API. (2) The API should allow you to generate female voices, however, it does not seem to be working at the moment. (3) This uses a Huggingface Gradio Space to compute via the API.
+    '''
+    client = Client("Flux9665/MassivelyMultilingualTTS")
+    result = client.predict(
+    		prompt=text,
+    		language=model,
+    		reference_audio=handle_file('https://github.com/gradio-app/gradio/raw/main/test/test_files/audio_sample.wav'),
+    		voice_seed=123,
+    		prosody_creativity=0.1,
+    		duration_scaling_factor=1,
+    		emb1=0,
+    		#emb2=0,
+    		api_name="/predict"
+    )
+    sampling_rate, wav = wavfile.read(result[0])
+    return wav, sampling_rate
+
+def synth_piper(text:str, model:str):
+    '''
+    Use Toucan to synthesize text.
+
+    Inputs:
+        text: Text to synthesze
+        model: Model code 
+    Returns:
+        Streaming Wav and sampling rate.
+
+    NOTES: (1) This uses a Huggingface Gradio Space to compute via the API.
+    '''
+    if model is not None:
+        client = Client("k2-fsa/text-to-speech")
+        result =  client.predict(
+        		language=model[0],
+        		repo_id=model[1],
+        		text=text,
+        		sid="0",
+        		speed=1,
+        		api_name="/process"
+        )
+        sampling_rate, wav = wavfile.read(result[0])
+        return wav, sampling_rate
+    else:
+        return None