diff --git a/dev-requirements.txt b/dev-requirements.txt
index c706d8fe6..92b6ec4d3 100644
--- a/dev-requirements.txt
+++ b/dev-requirements.txt
@@ -1,5 +1,5 @@
 build~=1.2.1
-grpcio-tools~=1.62.2
+grpcio-tools~=1.65.4
 pip-tools~=7.4.1
 pyright~=1.1.376
 pytest~=8.3.2
diff --git a/examples/foundational/01c-fastpitch.py b/examples/foundational/01c-fastpitch.py
new file mode 100644
index 000000000..49499cdfc
--- /dev/null
+++ b/examples/foundational/01c-fastpitch.py
@@ -0,0 +1,56 @@
+#
+# Copyright (c) 2024, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import aiohttp
+import os
+import sys
+
+from pipecat.frames.frames import EndFrame, TTSSpeakFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.task import PipelineTask
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.services.riva import FastpitchTTSService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+from runner import configure
+
+from loguru import logger
+
+from dotenv import load_dotenv
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (room_url, _) = await configure(session)
+
+        transport = DailyTransport(
+            room_url, None, "Say One Thing", DailyParams(audio_out_enabled=True)
+        )
+
+        tts = FastpitchTTSService(api_key=os.getenv("NVIDIA_API_KEY"))
+
+        runner = PipelineRunner()
+
+        task = PipelineTask(Pipeline([tts, transport.output()]))
+
+        # Register an event handler so we can play the audio when the
+        # participant joins.
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            participant_name = participant.get("info", {}).get("userName", "")
+            await task.queue_frames([TTSSpeakFrame(f"Aloha, {participant_name}!"), EndFrame()])
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
diff --git a/examples/foundational/07r-interruptible-riva-nim.py b/examples/foundational/07r-interruptible-riva-nim.py
new file mode 100644
index 000000000..09d261bc3
--- /dev/null
+++ b/examples/foundational/07r-interruptible-riva-nim.py
@@ -0,0 +1,92 @@
+#
+# Copyright (c) 2024, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import os
+import sys
+
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+from runner import configure
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMMessagesFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.services.nim import NimLLMService
+from pipecat.services.riva import FastpitchTTSService, ParakeetSTTService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (room_url, _) = await configure(session)
+
+        transport = DailyTransport(
+            room_url,
+            None,
+            "Respond bot",
+            DailyParams(
+                audio_out_enabled=True,
+                vad_enabled=True,
+                vad_analyzer=SileroVADAnalyzer(),
+                vad_audio_passthrough=True,
+            ),
+        )
+
+        stt = ParakeetSTTService(api_key=os.getenv("NVIDIA_API_KEY"))
+
+        llm = NimLLMService(
+            api_key=os.getenv("NVIDIA_API_KEY"), model="meta/llama-3.1-405b-instruct"
+        )
+
+        tts = FastpitchTTSService(api_key=os.getenv("NVIDIA_API_KEY"))
+
+        messages = [
+            {
+                "role": "system",
+                "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+            },
+        ]
+
+        context = OpenAILLMContext(messages)
+        context_aggregator = llm.create_context_aggregator(context)
+
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                stt,  # STT
+                context_aggregator.user(),  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                context_aggregator.assistant(),  # Assistant spoken responses
+            ]
+        )
+
+        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            # Kick off the conversation.
+            messages.append({"role": "system", "content": "Please introduce yourself to the user."})
+            await task.queue_frames([LLMMessagesFrame(messages)])
+
+        runner = PipelineRunner()
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
diff --git a/pyproject.toml b/pyproject.toml
index b2bd0c48f..549ecece8 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -25,7 +25,7 @@ dependencies = [
     "Markdown~=3.7",
     "numpy~=1.26.4",
     "Pillow~=10.4.0",
-    "protobuf~=4.25.4",
+    "protobuf~=5.26.1",
     "pydantic~=2.8.2",
     "pyloudnorm~=0.1.1",
     "resampy~=0.4.3",
@@ -48,7 +48,7 @@ elevenlabs = [ "websockets~=13.1" ]
 examples = [ "python-dotenv~=1.0.1", "flask~=3.0.3", "flask_cors~=4.0.1" ]
 fal = [ "fal-client~=0.4.1" ]
 gladia = [ "websockets~=13.1" ]
-google = [ "google-generativeai~=0.8.3", "google-cloud-texttospeech~=2.17.2" ]
+google = [ "google-generativeai~=0.8.3", "google-cloud-texttospeech~=2.21.1" ]
 grok = [ "openai~=1.50.2" ]
 groq = [ "openai~=1.50.2" ]
 gstreamer = [ "pygobject~=3.48.2" ]
@@ -63,7 +63,8 @@ nim = [ "openai~=1.50.2" ]
 noisereduce = [ "noisereduce~=3.0.3" ]
 openai = [ "openai~=1.50.2", "websockets~=13.1", "python-deepcompare~=1.0.1" ]
 openpipe = [ "openpipe~=4.38.0" ]
-playht = [ "pyht~=0.1.4", "websockets~=13.1" ]
+playht = [ "pyht~=0.1.8", "websockets~=13.1" ]
+riva = [ "nvidia-riva-client~=2.17.0" ]
 silero = [ "onnxruntime~=1.19.2" ]
 soundfile = [ "soundfile~=0.12.1" ]
 together = [ "openai~=1.50.2" ]
diff --git a/src/pipecat/services/riva.py b/src/pipecat/services/riva.py
new file mode 100644
index 000000000..0bbaee0ef
--- /dev/null
+++ b/src/pipecat/services/riva.py
@@ -0,0 +1,266 @@
+#
+# Copyright (c) 2024, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+from typing import AsyncGenerator, Optional
+
+from loguru import logger
+from pydantic.main import BaseModel
+
+from pipecat.frames.frames import (
+    CancelFrame,
+    EndFrame,
+    Frame,
+    InterimTranscriptionFrame,
+    StartFrame,
+    TranscriptionFrame,
+    TTSAudioRawFrame,
+    TTSStartedFrame,
+    TTSStoppedFrame,
+)
+from pipecat.services.ai_services import STTService, TTSService
+from pipecat.transcriptions.language import Language
+from pipecat.utils.time import time_now_iso8601
+
+try:
+    import riva.client
+
+except ModuleNotFoundError as e:
+    logger.error(f"Exception: {e}")
+    logger.error(
+        "In order to use nvidia riva TTS or STT, you need to `pip install pipecat-ai[riva]`. Also, set `NVIDIA_API_KEY` environment variable."
+    )
+    raise Exception(f"Missing module: {e}")
+
+
+class FastpitchTTSService(TTSService):
+    class InputParams(BaseModel):
+        language: Optional[Language] = Language.EN_US
+        quality: Optional[int] = 20
+
+    def __init__(
+        self,
+        *,
+        api_key: str,
+        server: str = "grpc.nvcf.nvidia.com:443",
+        voice_id: str = "English-US.Female-1",
+        sample_rate: int = 24000,
+        function_id: str = "0149dedb-2be8-4195-b9a0-e57e0e14f972",
+        params: InputParams = InputParams(),
+        **kwargs,
+    ):
+        super().__init__(sample_rate=sample_rate, **kwargs)
+        self._api_key = api_key
+        self._voice_id = voice_id
+        self._sample_rate = sample_rate
+        self._language_code = params.language
+        self._quality = params.quality
+
+        self.set_model_name("fastpitch-hifigan-tts")
+        self.set_voice(voice_id)
+
+        metadata = [
+            ["function-id", function_id],
+            ["authorization", f"Bearer {api_key}"],
+        ]
+        auth = riva.client.Auth(None, True, server, metadata)
+
+        self._service = riva.client.SpeechSynthesisService(auth)
+
+        # warm up the service
+        config_response = self._service.stub.GetRivaSynthesisConfig(
+            riva.client.proto.riva_tts_pb2.RivaSynthesisConfigRequest()
+        )
+
+    async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
+        def read_audio_responses():
+            try:
+                responses = self._service.synthesize_online(
+                    text,
+                    self._voice_id,
+                    self._language_code,
+                    sample_rate_hz=self._sample_rate,
+                    audio_prompt_file=None,
+                    quality=self._quality,
+                    custom_dictionary={},
+                )
+                return responses
+            except Exception as e:
+                logger.error(f"{self} exception: {e}")
+                return []
+
+        await self.start_ttfb_metrics()
+        yield TTSStartedFrame()
+
+        logger.debug(f"Generating TTS: [{text}]")
+        responses = await asyncio.to_thread(read_audio_responses)
+
+        for resp in responses:
+            await self.stop_ttfb_metrics()
+
+            frame = TTSAudioRawFrame(
+                audio=resp.audio,
+                sample_rate=self._sample_rate,
+                num_channels=1,
+            )
+            yield frame
+
+        await self.start_tts_usage_metrics(text)
+        yield TTSStoppedFrame()
+
+
+class ParakeetSTTService(STTService):
+    class InputParams(BaseModel):
+        language: Optional[Language] = Language.EN_US
+
+    def __init__(
+        self,
+        *,
+        api_key: str,
+        server: str = "grpc.nvcf.nvidia.com:443",
+        function_id: str = "1598d209-5e27-4d3c-8079-4751568b1081",
+        params: InputParams = InputParams(),
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+        self._api_key = api_key
+        self._profanity_filter = False
+        self._automatic_punctuation = False
+        self._no_verbatim_transcripts = False
+        self._language_code = params.language
+        self._boosted_lm_words = None
+        self._boosted_lm_score = 4.0
+        self._start_history = -1
+        self._start_threshold = -1.0
+        self._stop_history = -1
+        self._stop_threshold = -1.0
+        self._stop_history_eou = -1
+        self._stop_threshold_eou = -1.0
+        self._custom_configuration = ""
+        self._sample_rate: int = 16000
+
+        self.set_model_name("parakeet-ctc-1.1b-asr")
+
+        metadata = [
+            ["function-id", function_id],
+            ["authorization", f"Bearer {api_key}"],
+        ]
+        auth = riva.client.Auth(None, True, server, metadata)
+
+        self._asr_service = riva.client.ASRService(auth)
+
+        config = riva.client.StreamingRecognitionConfig(
+            config=riva.client.RecognitionConfig(
+                encoding=riva.client.AudioEncoding.LINEAR_PCM,
+                language_code=self._language_code,
+                model="",
+                max_alternatives=1,
+                profanity_filter=self._profanity_filter,
+                enable_automatic_punctuation=self._automatic_punctuation,
+                verbatim_transcripts=not self._no_verbatim_transcripts,
+                sample_rate_hertz=self._sample_rate,
+                audio_channel_count=1,
+            ),
+            interim_results=True,
+        )
+        riva.client.add_word_boosting_to_config(
+            config, self._boosted_lm_words, self._boosted_lm_score
+        )
+        riva.client.add_endpoint_parameters_to_config(
+            config,
+            self._start_history,
+            self._start_threshold,
+            self._stop_history,
+            self._stop_history_eou,
+            self._stop_threshold,
+            self._stop_threshold_eou,
+        )
+        riva.client.add_custom_configuration_to_config(config, self._custom_configuration)
+        self._config = config
+
+        self._queue = asyncio.Queue()
+
+    def can_generate_metrics(self) -> bool:
+        return False
+
+    async def start(self, frame: StartFrame):
+        await super().start(frame)
+        self._thread_task = self.get_event_loop().create_task(self._thread_task_handler())
+        self._response_task = self.get_event_loop().create_task(self._response_task_handler())
+        self._response_queue = asyncio.Queue()
+
+    async def stop(self, frame: EndFrame):
+        await super().stop(frame)
+        await self._stop_tasks()
+
+    async def cancel(self, frame: CancelFrame):
+        await super().cancel(frame)
+        await self._stop_tasks()
+
+    async def _stop_tasks(self):
+        self._thread_task.cancel()
+        await self._thread_task
+        self._response_task.cancel()
+        await self._response_task
+
+    def _response_handler(self):
+        responses = self._asr_service.streaming_response_generator(
+            audio_chunks=self,
+            streaming_config=self._config,
+        )
+        for response in responses:
+            if not response.results:
+                continue
+            asyncio.run_coroutine_threadsafe(
+                self._response_queue.put(response), self.get_event_loop()
+            )
+
+    async def _thread_task_handler(self):
+        try:
+            self._thread_running = True
+            await asyncio.to_thread(self._response_handler)
+        except asyncio.CancelledError:
+            self._thread_running = False
+            pass
+
+    async def _handle_response(self, response):
+        for result in response.results:
+            if result and not result.alternatives:
+                continue
+
+            transcript = result.alternatives[0].transcript
+            if transcript and len(transcript) > 0:
+                await self.stop_ttfb_metrics()
+                if result.is_final:
+                    await self.stop_processing_metrics()
+                    await self.push_frame(
+                        TranscriptionFrame(transcript, "", time_now_iso8601(), None)
+                    )
+                else:
+                    await self.push_frame(
+                        InterimTranscriptionFrame(transcript, "", time_now_iso8601(), None)
+                    )
+
+    async def _response_task_handler(self):
+        while True:
+            try:
+                response = await self._response_queue.get()
+                await self._handle_response(response)
+            except asyncio.CancelledError:
+                break
+
+    async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]:
+        await self._queue.put(audio)
+        yield None
+
+    def __next__(self) -> bytes:
+        if not self._thread_running:
+            raise StopIteration
+        future = asyncio.run_coroutine_threadsafe(self._queue.get(), self.get_event_loop())
+        return future.result()
+
+    def __iter__(self):
+        return self
diff --git a/test-requirements.txt b/test-requirements.txt
index 62be00385..f974121b0 100644
--- a/test-requirements.txt
+++ b/test-requirements.txt
@@ -7,8 +7,8 @@ deepgram-sdk~=3.5.0
 fal-client~=0.4.1
 fastapi~=0.115.0
 faster-whisper~=1.0.3
-google-cloud-texttospeech~=2.17.2
-google-generativeai~=0.7.2
+google-cloud-texttospeech~=2.21.1
+google-generativeai~=0.8.3
 langchain~=0.2.14
 livekit~=0.13.1
 lmnt~=1.1.4