updated ui, fixed audio inference thing, need to fix model selecting. ilaria tts added (#1)

- updated ui, fixed audio inference thing, need to fix model selecting. ilaria tts added (f7216ea4ce7b4821938cea9befa19e21112e5087)


Co-authored-by: Mikus <[email protected]>

app.py

@@ -1,209 +1,236 @@
-import gradio as gr
-import requests
-import random
-import os
-import zipfile # built in module for unzipping files (thank god)
-import librosa
-import time
-from infer_rvc_python import BaseLoader
-from pydub import AudioSegment
-
-# fucking dogshit toggle
-try:
-    import spaces
-    spaces_status = True
-except ImportError:
-    spaces_status = False
-
-converter = BaseLoader(only_cpu=False, hubert_path=None, rmvpe_path=None) # <- yeah so like this handles rvc
-
-global pth_file
-global index_file
-
-pth_file = "model.pth"
-index_file = "model.index"
-
-#CONFIGS
-TEMP_DIR = "temp"
-MODEL_PREFIX = "model"
-PITCH_ALGO_OPT = [
-    "pm",
-    "harvest",
-    "crepe",
-    "rmvpe",
-    "rmvpe+",
-]
-
-
-os.makedirs(TEMP_DIR, exist_ok=True)
-
-def unzip_file(file):
-    filename = os.path.basename(file).split(".")[0] # converts "model.zip" to "model" so we can do things
-    with zipfile.ZipFile(file, 'r') as zip_ref:
-        zip_ref.extractall(os.path.join(TEMP_DIR, filename)) # might not be very ram efficient...
-    return True
-    
-
-def progress_bar(total, current): # best progress bar ever trust me sunglasses emoji 😎 
-    return "[" + "=" * int(current / total * 20) + ">" + " " * (20 - int(current / total * 20)) + "] " + str(int(current / total * 100)) + "%"
-
-def download_from_url(url, filename=None):
-    if "huggingface" not in url:
-        return ["The URL must be from huggingface", "Failed", "Failed"]
-    if filename is None:
-        filename = os.path.join(TEMP_DIR, MODEL_PREFIX + str(random.randint(1, 1000)) + ".zip")
-    response = requests.get(url)
-    total = int(response.headers.get('content-length', 0)) # bytes to download (length of the file)
-    if total > 500000000:
-
-        return ["The file is too large. You can only download files up to 500 MB in size.", "Failed", "Failed"]
-    current = 0
-    with open(filename, "wb") as f:
-        for data in response.iter_content(chunk_size=4096): # download in chunks of 4096 bytes (4kb - helps with memory usage and speed)
-            f.write(data)
-            current += len(data)
-            print(progress_bar(total, current), end="\r") # \r is a carriage return, it moves the cursor to the start of the line so its like tqdm sunglasses emoji 😎
-    
-    # unzip because the model is in a zip file lel
-
-    try:
-        unzip_file(filename)
-    except Exception as e:
-        return ["Failed to unzip the file", "Failed", "Failed"] # return early if it fails and like tell the user but its dogshit hahahahahahaha 😎 According to all known laws aviation, there is no way a bee should be able to fly.
-    unzipped_dir = os.path.join(TEMP_DIR, os.path.basename(filename).split(".")[0]) # just do what we did in unzip_file because we need the directory
-    pth_files = []
-    index_files = []
-    for root, dirs, files in os.walk(unzipped_dir): # could be done more efficiently because nobody stores models in subdirectories but like who cares (it's a futureproofing thing lel)
-        for file in files:
-            if file.endswith(".pth"):
-                pth_files.append(os.path.join(root, file))
-            elif file.endswith(".index"):
-                index_files.append(os.path.join(root, file))
-    
-    print(pth_files, index_files) # debug print because im fucking stupid and i need to see what is going on
-    global pth_file
-    global index_file
-    pth_file = pth_files[0]
-    index_file = index_files[0]
-    return ["Downloaded as " + filename, pth_files[0], index_files[0]]
-
-if spaces_status:
-    @spaces.GPU()
-    def convert_now(audio_files, random_tag, converter):
-        return converter(
-            audio_files,
-            random_tag,
-            overwrite=False,
-            parallel_workers=8
-        )
-else:
-    def convert_now(audio_files, random_tag, converter):
-        return converter(
-            audio_files,
-            random_tag,
-            overwrite=False,
-            parallel_workers=8
-        )
-    
-def run(
-    audio_files,
-    file_m,
-    pitch_alg,
-    pitch_lvl,
-    file_index,
-    index_inf,
-    r_m_f,
-    e_r,
-    c_b_p,
-):
-    if not audio_files:
-        raise ValueError("The audio pls")
-
-    if isinstance(audio_files, str):
-        audio_files = [audio_files]
-
-    try:
-        duration_base = librosa.get_duration(filename=audio_files[0])
-        print("Duration:", duration_base)
-    except Exception as e:
-        print(e)
-
-    random_tag = "USER_"+str(random.randint(10000000, 99999999))
-
-    converter.apply_conf(
-        tag=random_tag,
-        file_model=file_m,
-        pitch_algo=pitch_alg,
-        pitch_lvl=pitch_lvl,
-        file_index=file_index,
-        index_influence=index_inf,
-        respiration_median_filtering=r_m_f,
-        envelope_ratio=e_r,
-        consonant_breath_protection=c_b_p,
-        resample_sr=44100 if audio_files[0].endswith('.mp3') else 0, 
-    )
-    time.sleep(0.1)
-
-    result = convert_now(audio_files, random_tag, converter)
-
-    return result[0]
-
-with gr.Blocks() as demo:
-    gr.Markdown("## Ilaria RVC 💖")
-    with gr.Tab("Inference"):
-        sound_gui = gr.Audio(value=None,type="filepath",autoplay=False,visible=True,)
-        pth_file_ui = gr.Textbox(label="Model pth file",value=pth_file,visible=False,interactive=False,) # gradio is fucking weird (im with stupid v)
-        index_file_ui = gr.Textbox(label="Index pth file",value=index_file,visible=False,interactive=False,) # gradio is fucking weird (im with stupid ^)
-        pitch_algo_conf = gr.Dropdown(PITCH_ALGO_OPT,value=PITCH_ALGO_OPT[4],label="Pitch algorithm",visible=True,interactive=True,)
-        pitch_lvl_conf = gr.Slider(label="Pitch level",minimum=-24,maximum=24,step=1,value=0,visible=True,interactive=True,)
-        index_inf_conf =  gr.Slider(minimum=0,maximum=1,label="Index influence",value=0.75,)
-        respiration_filter_conf = gr.Slider(minimum=0,maximum=7,label="Respiration median filtering",value=3,step=1,interactive=True,)
-        envelope_ratio_conf = gr.Slider(minimum=0,maximum=1,label="Envelope ratio",value=0.25,interactive=True,)
-        consonant_protec_conf = gr.Slider(minimum=0,maximum=0.5,label="Consonant breath protection",value=0.5,interactive=True,)
-        button_conf = gr.Button("Convert",variant="primary",)
-        output_conf = gr.Audio(type="filepath",label="Output",)
-
-        button_conf.click(
-            run,
-            inputs=[
-                sound_gui,
-                pth_file_ui,
-                pitch_algo_conf,
-                pitch_lvl_conf,
-                index_file_ui, # put a bullet through my head
-                index_inf_conf,
-                respiration_filter_conf,
-                envelope_ratio_conf,
-                consonant_protec_conf,
-            ],
-            outputs=[output_conf],
-        )
-    
-    with gr.Tab("Download Model"):
-        # markdown
-        gr.Markdown(
-            "Download the model from the following URL and upload it here. (Hugginface RVC model)"
-        )
-        model = gr.Textbox(lines=1, label="Model URL")
-        download_button = gr.Button("Download Model")
-        status = gr.Textbox(lines=1, label="Status", placeholder="Waiting....", interactive=False)
-        model_pth = gr.Textbox(lines=1, label="Model pth file", placeholder="Waiting....", interactive=False)
-        index_pth = gr.Textbox(lines=1, label="Index pth file", placeholder="Waiting....", interactive=False)
-        download_button.click(download_from_url, model, outputs=[status, model_pth, index_pth])
-        set_model_button = gr.Button("Set Model")
-        #set_model_button.click(
-
-    with gr.Tab("Credits"):
-        gr.Markdown(
-            """
-            Ilaria RVC made by [Ilaria](https://huggingface.co/TheStinger) suport her on [ko-fi](https://ko-fi.com/ilariaowo)
-            
-            The Inference code is made by [r3gm](https://huggingface.co/r3gm) (his module helped form this space 💖)
-
-            made with ❤️ by [mikus](https://github.com/cappuch) - i hacked it up lel
-
-            ### **In loving memory of JLabDX** 🕊️
-            """
-        )
-
-demo.queue(api_open=False).launch(show_api=False) # idk ilaria if you want or dont want to
+import gradio as gr
+import requests
+import random
+import os
+import zipfile # built in module for unzipping files (thank god)
+import librosa
+import time
+from infer_rvc_python import BaseLoader
+from pydub import AudioSegment
+from tts_voice import tts_order_voice
+import edge_tts
+import tempfile
+import anyio
+
+language_dict = tts_order_voice
+
+# ilaria tts implementation :rofl:
+async def text_to_speech_edge(text, language_code):
+    voice = language_dict[language_code]
+    communicate = edge_tts.Communicate(text, voice)
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp_file:
+        tmp_path = tmp_file.name
+
+    await communicate.save(tmp_path)
+
+    return tmp_path
+
+# fucking dogshit toggle
+try:
+    import spaces
+    spaces_status = True
+except ImportError:
+    spaces_status = False
+
+converter = BaseLoader(only_cpu=False, hubert_path=None, rmvpe_path=None) # <- yeah so like this handles rvc
+
+global pth_file
+global index_file
+
+pth_file = "model.pth"
+index_file = "model.index"
+
+#CONFIGS
+TEMP_DIR = "temp"
+MODEL_PREFIX = "model"
+PITCH_ALGO_OPT = [
+    "pm",
+    "harvest",
+    "crepe",
+    "rmvpe",
+    "rmvpe+",
+]
+
+
+os.makedirs(TEMP_DIR, exist_ok=True)
+
+def unzip_file(file):
+    filename = os.path.basename(file).split(".")[0] # converts "model.zip" to "model" so we can do things
+    with zipfile.ZipFile(file, 'r') as zip_ref:
+        zip_ref.extractall(os.path.join(TEMP_DIR, filename)) # might not be very ram efficient...
+    return True
+    
+
+def progress_bar(total, current): # best progress bar ever trust me sunglasses emoji 😎 
+    return "[" + "=" * int(current / total * 20) + ">" + " " * (20 - int(current / total * 20)) + "] " + str(int(current / total * 100)) + "%"
+
+def download_from_url(url, filename=None):
+    if "huggingface" not in url:
+        return ["The URL must be from huggingface", "Failed", "Failed"]
+    if filename is None:
+        filename = os.path.join(TEMP_DIR, MODEL_PREFIX + str(random.randint(1, 1000)) + ".zip")
+    response = requests.get(url)
+    total = int(response.headers.get('content-length', 0)) # bytes to download (length of the file)
+    if total > 500000000:
+
+        return ["The file is too large. You can only download files up to 500 MB in size.", "Failed", "Failed"]
+    current = 0
+    with open(filename, "wb") as f:
+        for data in response.iter_content(chunk_size=4096): # download in chunks of 4096 bytes (4kb - helps with memory usage and speed)
+            f.write(data)
+            current += len(data)
+            print(progress_bar(total, current), end="\r") # \r is a carriage return, it moves the cursor to the start of the line so its like tqdm sunglasses emoji 😎
+    
+    # unzip because the model is in a zip file lel
+
+    try:
+        unzip_file(filename)
+    except Exception as e:
+        return ["Failed to unzip the file", "Failed", "Failed"] # return early if it fails and like tell the user but its dogshit hahahahahahaha 😎 According to all known laws aviation, there is no way a bee should be able to fly.
+    unzipped_dir = os.path.join(TEMP_DIR, os.path.basename(filename).split(".")[0]) # just do what we did in unzip_file because we need the directory
+    pth_files = []
+    index_files = []
+    for root, dirs, files in os.walk(unzipped_dir): # could be done more efficiently because nobody stores models in subdirectories but like who cares (it's a futureproofing thing lel)
+        for file in files:
+            if file.endswith(".pth"):
+                pth_files.append(os.path.join(root, file))
+            elif file.endswith(".index"):
+                index_files.append(os.path.join(root, file))
+    
+    print(pth_files, index_files) # debug print because im fucking stupid and i need to see what is going on
+    global pth_file
+    global index_file
+    pth_file = pth_files[0]
+    index_file = index_files[0]
+    return ["Downloaded as " + filename, pth_files[0], index_files[0]]
+
+if spaces_status:
+    @spaces.GPU()
+    def convert_now(audio_files, random_tag, converter):
+        return converter(
+            audio_files,
+            random_tag,
+            overwrite=False,
+            parallel_workers=8
+        )
+else:
+    def convert_now(audio_files, random_tag, converter):
+        return converter(
+            audio_files,
+            random_tag,
+            overwrite=False,
+            parallel_workers=8
+        )
+    
+def run(
+    audio_files,
+    file_m,
+    pitch_alg,
+    pitch_lvl,
+    file_index,
+    index_inf,
+    r_m_f,
+    e_r,
+    c_b_p,
+):
+    if not audio_files:
+        raise ValueError("The audio pls")
+
+    if isinstance(audio_files, str):
+        audio_files = [audio_files]
+
+    try:
+        duration_base = librosa.get_duration(filename=audio_files[0])
+        print("Duration:", duration_base)
+    except Exception as e:
+        print(e)
+
+    random_tag = "USER_"+str(random.randint(10000000, 99999999))
+
+    converter.apply_conf(
+        tag=random_tag,
+        file_model=file_m,
+        pitch_algo=pitch_alg,
+        pitch_lvl=pitch_lvl,
+        file_index=file_index,
+        index_influence=index_inf,
+        respiration_median_filtering=r_m_f,
+        envelope_ratio=e_r,
+        consonant_breath_protection=c_b_p,
+        resample_sr=44100 if audio_files[0].endswith('.mp3') else 0, 
+    )
+    time.sleep(0.1)
+
+    result = convert_now(audio_files, random_tag, converter)
+
+    return result[0]
+
+with gr.Blocks() as demo:
+    gr.Markdown("## Ilaria RVC 💖")
+    with gr.Tab("Inference"):
+        with gr.Tab("Ilaria TTS"):
+            text_tts = gr.Textbox(label="Text", placeholder="Hello!", lines=3, interactive=True,)
+            dropdown_tts = gr.Dropdown(label="Language and Model",choices=list(language_dict.keys()),interactive=True, value=list(language_dict.keys())[0])
+            
+            button_tts = gr.Button("Convert", variant="primary",)
+
+            output_tts = gr.Audio(type="filepath", label="Output",)
+
+            button_tts.click(text_to_speech_edge, inputs=[text_tts, dropdown_tts], outputs=[output_tts])
+            
+
+        sound_gui = gr.Audio(value=None,type="filepath",autoplay=False,visible=True,)
+        pth_file_ui = gr.Textbox(label="Model pth file",value=pth_file,visible=False,interactive=False,) # gradio is fucking weird (im with stupid v)
+        index_file_ui = gr.Textbox(label="Index pth file",value=index_file,visible=False,interactive=False,) # gradio is fucking weird (im with stupid ^)
+        pitch_algo_conf = gr.Dropdown(PITCH_ALGO_OPT,value=PITCH_ALGO_OPT[4],label="Pitch algorithm",visible=True,interactive=True,)
+        pitch_lvl_conf = gr.Slider(label="Pitch level",minimum=-24,maximum=24,step=1,value=0,visible=True,interactive=True,)
+        index_inf_conf =  gr.Slider(minimum=0,maximum=1,label="Index influence",value=0.75,)
+        respiration_filter_conf = gr.Slider(minimum=0,maximum=7,label="Respiration median filtering",value=3,step=1,interactive=True,)
+        envelope_ratio_conf = gr.Slider(minimum=0,maximum=1,label="Envelope ratio",value=0.25,interactive=True,)
+        consonant_protec_conf = gr.Slider(minimum=0,maximum=0.5,label="Consonant breath protection",value=0.5,interactive=True,)
+        button_conf = gr.Button("Convert",variant="primary",)
+        output_conf = gr.Audio(type="filepath",label="Output",)
+    	
+        button_conf.click(lambda :None, None, output_conf)
+        button_conf.click(
+            run,
+            inputs=[
+                sound_gui,
+                pth_file_ui,
+                pitch_algo_conf,
+                pitch_lvl_conf,
+                index_file_ui, # put a bullet through my head
+                index_inf_conf,
+                respiration_filter_conf,
+                envelope_ratio_conf,
+                consonant_protec_conf,
+            ],
+            outputs=[output_conf],
+        )
+    
+    with gr.Tab("Download Model"):
+        # markdown
+        gr.Markdown(
+            "Download the model from the following URL and upload it here. (Hugginface RVC model)"
+        )
+        model = gr.Textbox(lines=1, label="Model URL")
+        download_button = gr.Button("Download Model")
+        status = gr.Textbox(lines=1, label="Status", placeholder="Waiting....", interactive=False)
+        model_pth = gr.Textbox(lines=1, label="Model pth file", placeholder="Waiting....", interactive=False)
+        index_pth = gr.Textbox(lines=1, label="Index pth file", placeholder="Waiting....", interactive=False)
+        download_button.click(download_from_url, model, outputs=[status, model_pth, index_pth])
+        set_model_button = gr.Button("Set Model")
+        #set_model_button.click(
+
+    with gr.Tab("Credits"):
+        gr.Markdown(
+            """
+            Ilaria RVC made by [Ilaria](https://huggingface.co/TheStinger) suport her on [ko-fi](https://ko-fi.com/ilariaowo)
+            
+            The Inference code is made by [r3gm](https://huggingface.co/r3gm) (his module helped form this space 💖)
+
+            made with ❤️ by [mikus](https://github.com/cappuch) - i hacked it up lel
+            """
+        )
+
+demo.queue(api_open=False).launch(show_api=False) # idk ilaria if you want or dont want to

tts_voice.py

@@ -0,0 +1,230 @@
+tts_order_voice = {'English-Jenny (Woman)': 'en-US-JennyNeural',
+ 'English-Guy (Man)': 'en-US-GuyNeural',
+ 'English-Ana (Woman)': 'en-US-AnaNeural',
+ 'English-Aria (Woman)': 'en-US-AriaNeural',
+ 'English-Christopher (Man)': 'en-US-ChristopherNeural',
+ 'English-Eric (Man)': 'en-US-EricNeural',
+ 'English-Michelle (Woman)': 'en-US-MichelleNeural',
+ 'English-Roger (Man)': 'en-US-RogerNeural',
+ 'Spanish (Mexican)-Dalia (Woman)': 'es-MX-DaliaNeural',
+ 'Spanish (Mexican)-Jorge- (Man)': 'es-MX-JorgeNeural',
+ 'Korean-Sun-Hi- (Woman)': 'ko-KR-SunHiNeural',
+ 'Korean-InJoon- (Man)': 'ko-KR-InJoonNeural',
+'Thai-Premwadee- (Woman)': 'th-TH-PremwadeeNeural',
+ 'Thai-Niwat- (Man)': 'th-TH-NiwatNeural',
+ 'Vietnamese-HoaiMy- (Woman)': 'vi-VN-HoaiMyNeural',
+'Vietnamese-NamMinh- (Man)': 'vi-VN-NamMinhNeural',
+ 'Japanese-Nanami- (Woman)': 'ja-JP-NanamiNeural',
+ 'Japanese-Keita- (Man)': 'ja-JP-KeitaNeural',
+ 'French-Denise- (Woman)': 'fr-FR-DeniseNeural',
+ 'French-Eloise- (Woman)': 'fr-FR-EloiseNeural',
+ 'French-Henri- (Man)': 'fr-FR-HenriNeural',
+ 'Brazilian-Francisca- (Woman)': 'pt-BR-FranciscaNeural',
+ 'Brazilian-Antonio- (Man)': 'pt-BR-AntonioNeural',
+ 'Indonesian-Ardi- (Man)': 'id-ID-ArdiNeural',
+ 'Indonesian-Gadis- (Woman)': 'id-ID-GadisNeural',
+ 'Hebrew-Avri- (Man)': 'he-IL-AvriNeural',
+ 'Hebrew-Hila- (Woman)': 'he-IL-HilaNeural',
+'Italian-Isabella- (Woman)': 'it-IT-IsabellaNeural',
+ 'Italian-Diego- (Man)': 'it-IT-DiegoNeural',
+ 'Italian-Elsa- (Woman)': 'it-IT-ElsaNeural',
+ 'Dutch-Colette- (Woman)': 'nl-NL-ColetteNeural',
+ 'Dutch-Fenna- (Woman)': 'nl-NL-FennaNeural',
+ 'Dutch-Maarten- (Man)': 'nl-NL-MaartenNeural',
+'Malese-Osman- (Man)': 'ms-MY-OsmanNeural',
+ 'Malese-Yasmin- (Woman)': 'ms-MY-YasminNeural',
+ 'Norwegian-Pernille- (Woman)': 'nb-NO-PernilleNeural',
+ 'Norwegian-Finn- (Man)': 'nb-NO-FinnNeural',
+ 'Swedish-Sofie- (Woman)': 'sv-SE-SofieNeural',
+ 'ArabicSwedish-Mattias- (Man)': 'sv-SE-MattiasNeural',
+ 'Arabic-Hamed- (Man)': 'ar-SA-HamedNeural',
+ 'Arabic-Zariyah- (Woman)': 'ar-SA-ZariyahNeural',
+ 'Greek-Athina- (Woman)': 'el-GR-AthinaNeural',
+ 'Greek-Nestoras- (Man)': 'el-GR-NestorasNeural',
+'German-Katja- (Woman)': 'de-DE-KatjaNeural',
+ 'German-Amala- (Woman)': 'de-DE-AmalaNeural',
+ 'German-Conrad- (Man)': 'de-DE-ConradNeural',
+ 'German-Killian- (Man)': 'de-DE-KillianNeural',
+ 'Afrikaans-Adri- (Woman)': 'af-ZA-AdriNeural',
+ 'Afrikaans-Willem- (Man)': 'af-ZA-WillemNeural',
+ 'Ethiopian-Ameha- (Man)': 'am-ET-AmehaNeural',
+ 'Ethiopian-Mekdes- (Woman)': 'am-ET-MekdesNeural',
+ 'Arabic (UAD)-Fatima- (Woman)': 'ar-AE-FatimaNeural',
+ 'Arabic (UAD)-Hamdan- (Man)': 'ar-AE-HamdanNeural',
+ 'Arabic (Bahrain)-Ali- (Man)': 'ar-BH-AliNeural',
+ 'Arabic (Bahrain)-Laila- (Woman)': 'ar-BH-LailaNeural',
+ 'Arabic (Algeria)-Ismael- (Man)': 'ar-DZ-IsmaelNeural',
+ 'Arabic (Egypt)-Salma- (Woman)': 'ar-EG-SalmaNeural',
+ 'Arabic (Egypt)-Shakir- (Man)': 'ar-EG-ShakirNeural',
+ 'Arabic (Iraq)-Bassel- (Man)': 'ar-IQ-BasselNeural',
+ 'Arabic (Iraq)-Rana- (Woman)': 'ar-IQ-RanaNeural',
+ 'Arabic (Jordan)-Sana- (Woman)': 'ar-JO-SanaNeural',
+ 'Arabic (Jordan)-Taim- (Man)': 'ar-JO-TaimNeural',
+ 'Arabic (Kuwait)-Fahed- (Man)': 'ar-KW-FahedNeural',
+ 'Arabic (Kuwait)-Noura- (Woman)': 'ar-KW-NouraNeural',
+ 'Arabic (Lebanon)-Layla- (Woman)': 'ar-LB-LaylaNeural',
+ 'Arabic (Lebanon)-Rami- (Man)': 'ar-LB-RamiNeural',
+ 'Arabic (Libya)-Iman- (Woman)': 'ar-LY-ImanNeural',
+ 'Arabic (Libya)-Omar- (Man)': 'ar-LY-OmarNeural',
+ 'Arabic (Morocco)-Jamal- (Man)': 'ar-MA-JamalNeural',
+ 'Arabic (Morocco)-Mouna- (Woman)': 'ar-MA-MounaNeural',
+ 'Arabic (Oman)-Abdullah- (Man)': 'ar-OM-AbdullahNeural',
+ 'Arabic (Oman)-Aysha- (Woman)': 'ar-OM-AyshaNeural',
+ 'Arabic (Qatar)-Amal- (Woman)': 'ar-QA-AmalNeural',
+ 'Arabic (Qatar)-Moaz- (Man)': 'ar-QA-MoazNeural',
+ 'Arabic (Syrian Arab Republic)-Amany- (Woman)': 'ar-SY-AmanyNeural',
+ 'Arabic (Syrian Arab Republic)-Laith- (Man)': 'ar-SY-LaithNeural',
+ 'Arabic (Tunisia)-Hedi- (Man)': 'ar-TN-HediNeural',
+ 'Arabic (Tunisia)-Reem- (Woman)': 'ar-TN-ReemNeural',
+ 'Arabic (Yemen	)-Maryam- (Woman)': 'ar-YE-MaryamNeural',
+ 'Arabic (Yemen	)-Saleh- (Man)': 'ar-YE-SalehNeural',
+ 'Azerbaijani-Babek- (Man)': 'az-AZ-BabekNeural',
+ 'Azerbaijani-Banu- (Woman)': 'az-AZ-BanuNeural',
+ 'Bulgarian-Borislav- (Man)': 'bg-BG-BorislavNeural',
+ 'Bulgarian-Kalina- (Woman)': 'bg-BG-KalinaNeural',
+ 'Bengali (Bangladesh)-Nabanita- (Woman)': 'bn-BD-NabanitaNeural',
+ 'Bengali (Bangladesh)-Pradeep- (Man)': 'bn-BD-PradeepNeural',
+ 'Bengali (India)-Bashkar- (Man)': 'bn-IN-BashkarNeural',
+ 'Bengali (India)-Tanishaa- (Woman)': 'bn-IN-TanishaaNeural',
+ 'Bosniak (Bosnia and Herzegovina)-Goran- (Man)': 'bs-BA-GoranNeural',
+ 'Bosniak (Bosnia and Herzegovina)-Vesna- (Woman)': 'bs-BA-VesnaNeural',
+ 'Catalan (Spain)-Joana- (Woman)': 'ca-ES-JoanaNeural',
+ 'Catalan (Spain)-Enric- (Man)': 'ca-ES-EnricNeural',
+ 'Czech (Czech Republic)-Antonin- (Man)': 'cs-CZ-AntoninNeural',
+ 'Czech (Czech Republic)-Vlasta- (Woman)': 'cs-CZ-VlastaNeural',
+ 'Welsh (UK)-Aled- (Man)': 'cy-GB-AledNeural',
+ 'Welsh (UK)-Nia- (Woman)': 'cy-GB-NiaNeural',
+ 'Danish (Denmark)-Christel- (Woman)': 'da-DK-ChristelNeural',
+ 'Danish (Denmark)-Jeppe- (Man)': 'da-DK-JeppeNeural',
+ 'German (Austria)-Ingrid- (Woman)': 'de-AT-IngridNeural',
+ 'German (Austria)-Jonas- (Man)': 'de-AT-JonasNeural',
+ 'German (Switzerland)-Jan- (Man)': 'de-CH-JanNeural',
+ 'German (Switzerland)-Leni- (Woman)': 'de-CH-LeniNeural',
+ 'English (Australia)-Natasha- (Woman)': 'en-AU-NatashaNeural',
+ 'English (Australia)-William- (Man)': 'en-AU-WilliamNeural',
+ 'English (Canada)-Clara- (Woman)': 'en-CA-ClaraNeural',
+ 'English (Canada)-Liam- (Man)': 'en-CA-LiamNeural',
+ 'English (UK)-Libby- (Woman)': 'en-GB-LibbyNeural',
+ 'English (UK)-Maisie- (Woman)': 'en-GB-MaisieNeural',
+ 'English (UK)-Ryan- (Man)': 'en-GB-RyanNeural',
+ 'English (UK)-Sonia- (Woman)': 'en-GB-SoniaNeural',
+ 'English (UK)-Thomas- (Man)': 'en-GB-ThomasNeural',
+ 'English (Hong Kong)-Sam- (Man)': 'en-HK-SamNeural',
+ 'English (Hong Kong)-Yan- (Woman)': 'en-HK-YanNeural',
+ 'English (Ireland)-Connor- (Man)': 'en-IE-ConnorNeural',
+ 'English (Ireland)-Emily- (Woman)': 'en-IE-EmilyNeural',
+ 'English (India)-Neerja- (Woman)': 'en-IN-NeerjaNeural',
+ 'English (India)-Prabhat- (Man)': 'en-IN-PrabhatNeural',
+ 'English (Kenya)-Asilia- (Woman)': 'en-KE-AsiliaNeural',
+ 'English (Kenya)-Chilemba- (Man)': 'en-KE-ChilembaNeural',
+ 'English (Nigeria)-Abeo- (Man)': 'en-NG-AbeoNeural',
+'English (Nigeria)-Ezinne- (Woman)': 'en-NG-EzinneNeural',
+ 'English (New Zealand)-Mitchell- (Man)': 'en-NZ-MitchellNeural',
+ 'English (Philippines)-James- (Man)': 'en-PH-JamesNeural',
+ 'English (Philippines)-Rosa- (Woman)': 'en-PH-RosaNeural',
+ 'English (Singapore)-Luna- (Woman)': 'en-SG-LunaNeural',
+ 'English (Singapore)-Wayne- (Man)': 'en-SG-WayneNeural',
+ 'English (Tanzania)-Elimu- (Man)': 'en-TZ-ElimuNeural',
+ 'English (Tanzania)-Imani- (Woman)': 'en-TZ-ImaniNeural',
+ 'English (South Africa)-Leah- (Woman)': 'en-ZA-LeahNeural',
+ 'English (South Africa)-Luke- (Man)': 'en-ZA-LukeNeural',
+'Spanish (Argentina)-Elena- (Woman)': 'es-AR-ElenaNeural',
+ 'Spanish (Argentina)-Tomas- (Man)': 'es-AR-TomasNeural',
+ 'Spanish (Bolivia)-Marcelo- (Man)': 'es-BO-MarceloNeural',
+ 'Spanish (Bolivia)-Sofia- (Woman)': 'es-BO-SofiaNeural',
+ 'Spanish (Colombia)-Gonzalo- (Man)': 'es-CO-GonzaloNeural',
+ 'Spanish (Colombia)-Salome- (Woman)': 'es-CO-SalomeNeural',
+ 'Spanish (Costa Rica)-Juan- (Man)': 'es-CR-JuanNeural',
+ 'Spanish (Costa Rica)-Maria- (Woman)': 'es-CR-MariaNeural',
+ 'Spanish (Cuba)-Belkys- (Woman)': 'es-CU-BelkysNeural',
+ 'Spanish (Dominican Republic)-Emilio- (Man)': 'es-DO-EmilioNeural',
+ 'Spanish (Dominican Republic)-Ramona- (Woman)': 'es-DO-RamonaNeural',
+ 'Spanish (Ecuador)-Andrea- (Woman)': 'es-EC-AndreaNeural',
+ 'Spanish (Ecuador)-Luis- (Man)': 'es-EC-LuisNeural',
+ 'Spanish (Spain)-Alvaro- (Man)': 'es-ES-AlvaroNeural',
+ 'Spanish (Spain)-Elvira- (Woman)': 'es-ES-ElviraNeural',
+ 'Spanish (Equatorial Guinea)-Teresa- (Woman)': 'es-GQ-TeresaNeural',
+ 'Spanish (Guatemala)-Andres- (Man)': 'es-GT-AndresNeural',
+ 'Spanish (Guatemala)-Marta- (Woman)': 'es-GT-MartaNeural',
+ 'Spanish (Honduras)-Carlos- (Man)': 'es-HN-CarlosNeural',
+ 'Spanish (Honduras)-Karla- (Woman)': 'es-HN-KarlaNeural',
+ 'Spanish (Nicaragua)-Federico- (Man)': 'es-NI-FedericoNeural',
+ 'Spanish (Nicaragua)-Yolanda- (Woman)': 'es-NI-YolandaNeural',
+ 'Spanish (Panama)-Margarita- (Woman)': 'es-PA-MargaritaNeural',
+ 'Spanish (Panama)-Roberto- (Man)': 'es-PA-RobertoNeural',
+ 'Spanish (Peru)-Alex- (Man)': 'es-PE-AlexNeural',
+ 'Spanish (Peru)-Camila- (Woman)': 'es-PE-CamilaNeural',
+ 'Spanish (Puerto Rico)-Karina- (Woman)': 'es-PR-KarinaNeural',
+ 'Spanish (Puerto Rico)-Victor- (Man)': 'es-PR-VictorNeural',
+ 'Spanish (Paraguay)-Mario- (Man)': 'es-PY-MarioNeural',
+ 'Spanish (Paraguay)-Tania- (Woman)': 'es-PY-TaniaNeural',
+ 'Spanish (El Salvador)-Lorena- (Woman)': 'es-SV-LorenaNeural',
+ 'Spanish (El Salvador)-Rodrigo- (Man)': 'es-SV-RodrigoNeural',
+ 'Spanish (United States)-Alonso- (Man)': 'es-US-AlonsoNeural',
+ 'Spanish (United States)-Paloma- (Woman)': 'es-US-PalomaNeural',
+ 'Spanish (Uruguay)-Mateo- (Man)': 'es-UY-MateoNeural',
+ 'Spanish (Uruguay)-Valentina- (Woman)': 'es-UY-ValentinaNeural',
+ 'Spanish (Venezuela)-Paola- (Woman)': 'es-VE-PaolaNeural',
+ 'Spanish (Venezuela)-Sebastian- (Man)': 'es-VE-SebastianNeural',
+'Estonian (Estonia)-Anu- (Woman)': 'et-EE-AnuNeural',
+'Estonian (Estonia)-Kert- (Man)': 'et-EE-KertNeural',
+'Persian (Iran)-Dilara- (Woman)': 'fa-IR-DilaraNeural',
+'Persian (Iran)-Farid- (Man)': 'fa-IR-FaridNeural',
+'Finnish (Finland)-Harri- (Man)': 'fi-FI-HarriNeural',
+'Finnish (Finland)-Noora- (Woman)': 'fi-FI-NooraNeural',
+'French (Belgium)-Charline- (Woman)': 'fr-BE-CharlineNeural',
+'French (Belgium)-Gerard- (Man)': 'fr-BE-GerardNeural',
+'French (Canada)-Sylvie- (Woman)': 'fr-CA-SylvieNeural',
+'French (Canada)-Antoine- (Man)': 'fr-CA-AntoineNeural',
+'French (Canada)-Jean- (Man)': 'fr-CA-JeanNeural',
+'French (Switzerland)-Ariane- (Woman)': 'fr-CH-ArianeNeural',
+'French (Switzerland)-Fabrice- (Man)': 'fr-CH-FabriceNeural',
+'Irish (Ireland)-Colm- (Man)': 'ga-IE-ColmNeural',
+'Irish (Ireland)-Orla- (Woman)': 'ga-IE-OrlaNeural',
+'Galician (Spain)-Roi- (Man)': 'gl-ES-RoiNeural',
+'Galician (Spain)-Sabela- (Woman)': 'gl-ES-SabelaNeural',
+'Gujarati (India)-Dhwani- (Woman)': 'gu-IN-DhwaniNeural',
+'Gujarati (India)-Niranjan- (Man)': 'gu-IN-NiranjanNeural',
+'Hindi (India)-Madhur- (Man)': 'hi-IN-MadhurNeural',
+'Hindi (India)-Swara- (Woman)': 'hi-IN-SwaraNeural',
+'Croatian (Croatia)-Gabrijela- (Woman)': 'hr-HR-GabrijelaNeural',
+'Croatian (Croatia)-Srecko- (Man)': 'hr-HR-SreckoNeural',
+'Hungarian (Hungary)-Noemi- (Woman)': 'hu-HU-NoemiNeural',
+'Hungarian (Hungary)-Tamas- (Man)': 'hu-HU-TamasNeural',
+'Icelandic (Iceland)-Gudrun- (Woman)': 'is-IS-GudrunNeural',
+'Icelandic (Iceland)-Gunnar- (Man)': 'is-IS-GunnarNeural',
+'Javanese (Indonesia)-Dimas- (Man)': 'jv-ID-DimasNeural',
+'Javanese (Indonesia)-Siti- (Woman)': 'jv-ID-SitiNeural',
+'Georgian (Georgia)-Eka- (Woman)': 'ka-GE-EkaNeural',
+'Georgian (Georgia)-Giorgi- (Man)': 'ka-GE-GiorgiNeural',
+'Kazakh (Kazakhstan)-Aigul- (Woman)': 'kk-KZ-AigulNeural',
+'Kazakh (Kazakhstan)-Daulet- (Man)': 'kk-KZ-DauletNeural',
+'Khmer (Cambodia)-Piseth- (Man)': 'km-KH-PisethNeural',
+'Khmer (Cambodia)-Sreymom- (Woman)': 'km-KH-SreymomNeural',
+'Kannada (India)-Gagan- (Man)': 'kn-IN-GaganNeural',
+'Kannada (India)-Sapna- (Woman)': 'kn-IN-SapnaNeural',
+'Lao (Laos)-Chanthavong- (Man)': 'lo-LA-ChanthavongNeural',
+'Lao (Laos)-Keomany- (Woman)': 'lo-LA-KeomanyNeural',
+'Lithuanian (Lithuania)-Leonas- (Man)': 'lt-LT-LeonasNeural',
+'Lithuanian (Lithuania)-Ona- (Woman)': 'lt-LT-OnaNeural',
+'Latvian (Latvia)-Everita- (Woman)': 'lv-LV-EveritaNeural',
+'Latvian (Latvia)-Nils- (Man)': 'lv-LV-NilsNeural',
+'Macedonian (North Macedonia)-Aleksandar- (Man)': 'mk-MK-AleksandarNeural',
+'Macedonian (North Macedonia)-Marija- (Woman)': 'mk-MK-MarijaNeural',
+'Malayalam (India)-Midhun- (Man)': 'ml-IN-MidhunNeural',
+'Malayalam (India)-Sobhana- (Woman)': 'ml-IN-SobhanaNeural',
+'Mongolian (Mongolia)-Bataa- (Man)': 'mn-MN-BataaNeural',
+'Mongolian (Mongolia)-Yesui- (Woman)': 'mn-MN-YesuiNeural',
+'Marathi (India)-Aarohi- (Woman)': 'mr-IN-AarohiNeural',
+'Marathi (India)-Manohar- (Man)': 'mr-IN-ManoharNeural',
+'Maltese (Malta)-Grace- (Woman)': 'mt-MT-GraceNeural',
+'Maltese (Malta)-Joseph- (Man)': 'mt-MT-JosephNeural',
+'Burmese (Myanmar)-Nilar- (Woman)': 'my-MM-NilarNeural',
+'Burmese (Myanmar)-Thiha- (Man)': 'my-MM-ThihaNeural',
+'Nepali (Nepal)-Hemkala- (Woman)': 'ne-NP-HemkalaNeural',
+'Nepali (Nepal)-Sagar- (Man)': 'ne-NP-SagarNeural',
+'Dutch (Belgium)-Arnaud- (Man)': 'nl-BE-ArnaudNeural',
+'Dutch (Belgium)-Dena- (Woman)': 'nl-BE-DenaNeural',
+'Polish (Poland)-Marek- (Man)': 'pl-PL-MarekNeural',
+'Polish (Poland)-Zofia- (Woman)': 'pl-PL-ZofiaNeural',
+'Pashto (Afghanistan)-Gul Nawaz- (Man)': 'ps-AF-Gul',}