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jasper-asr
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Code Issues Releases Wiki Activity

1. removed the transcriber_pretrained/speller from utils 

2. introduced get_mongo_coll to get the collection object directly from mongo uri
3. removed processing of correction entries to remove space/upper casing
Malar Kannan 2020-06-04 17:49:16 +05:30
parent e3a01169c2
commit bca227a7d7
5 changed files with 42 additions and 50 deletions
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6
jasper/client.py
View File

@ -1,6 +1,7 @@
import os
import logging
import rpyc
from functools import lru_cache
logging.basicConfig(
level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
@ -12,12 +13,9 @@ ASR_HOST = os.environ.get("JASPER_ASR_RPYC_HOST", "localhost")
ASR_PORT = int(os.environ.get("JASPER_ASR_RPYC_PORT", "8045"))
@lru_cache()
def transcribe_gen(asr_host=ASR_HOST, asr_port=ASR_PORT):
logger.info(f"connecting to asr server at {asr_host}:{asr_port}")
asr = rpyc.connect(asr_host, asr_port).root
logger.info(f"connected to asr server successfully")
return asr.transcribe
transcriber_pretrained = transcribe_gen(asr_port=8044)
transcriber_speller = transcribe_gen(asr_port=8045)

47
jasper/data/call_recycler.py
View File

@ -1,15 +1,7 @@
# import argparse
# import logging
import typer
from pathlib import Path
app = typer.Typer()
# leader_app = typer.Typer()
# app.add_typer(leader_app, name="leaderboard")
# plot_app = typer.Typer()
# app.add_typer(plot_app, name="plot")
@app.command()
def export_all_logs(call_logs_file: Path = Path("./call_sia_logs.yaml")):
@ -18,7 +10,7 @@ def export_all_logs(call_logs_file: Path = Path("./call_sia_logs.yaml")):
from ruamel.yaml import YAML
yaml = YAML()
mongo_coll = get_mongo_conn().test.calls
mongo_coll = get_mongo_conn()
caller_calls = defaultdict(lambda: [])
for call in mongo_coll.find():
sysid = call["SystemID"]
@ -46,7 +38,7 @@ def export_calls_between(
from .utils import get_mongo_conn
yaml = YAML()
mongo_coll = get_mongo_conn(port=mongo_port).test.calls
mongo_coll = get_mongo_conn(port=mongo_port)
start_meta = mongo_coll.find_one({"SystemID": start_cid})
end_meta = mongo_coll.find_one({"SystemID": end_cid})
@ -77,23 +69,21 @@ def analyze(
plot_calls: bool = False,
extract_data: bool = False,
download_only: bool = False,
call_logs_file: Path = Path("./call_logs.yaml"),
call_logs_file: Path = typer.Option(Path("./call_logs.yaml"), show_default=True),
output_dir: Path = Path("./data"),
mongo_port: int = 27017,
data_name: str = None,
mongo_uri: str = typer.Option("mongodb://localhost:27017/test.calls", show_default=True),
):
from urllib.parse import urlsplit
from functools import reduce
import boto3
from io import BytesIO
import json
from ruamel.yaml import YAML
import re
from google.protobuf.timestamp_pb2 import Timestamp
from datetime import timedelta
# from concurrent.futures import ThreadPoolExecutor
import librosa
import librosa.display
from lenses import lens
@ -102,23 +92,17 @@ def analyze(
import matplotlib.pyplot as plt
import matplotlib
from tqdm import tqdm
from .utils import asr_data_writer, get_mongo_conn
from .utils import asr_data_writer, get_mongo_coll
from pydub import AudioSegment
from natural.date import compress
# from itertools import product, chain
matplotlib.rcParams["agg.path.chunksize"] = 10000
matplotlib.use("agg")
# logging.basicConfig(
# level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
# )
# logger = logging.getLogger(__name__)
yaml = YAML()
s3 = boto3.client("s3")
mongo_collection = get_mongo_conn(port=mongo_port).test.calls
mongo_collection = get_mongo_coll(mongo_uri)
call_media_dir: Path = output_dir / Path("call_wavs")
call_media_dir.mkdir(exist_ok=True, parents=True)
call_meta_dir: Path = output_dir / Path("call_metas")
@ -127,6 +111,7 @@ def analyze(
call_plot_dir.mkdir(exist_ok=True, parents=True)
call_asr_data: Path = output_dir / Path("asr_data")
call_asr_data.mkdir(exist_ok=True, parents=True)
dataset_name = call_logs_file.stem if not data_name else data_name
call_logs = yaml.load(call_logs_file.read_text())
@ -183,7 +168,7 @@ def analyze(
call_events = call_meta["Events"]
def is_writer_uri_event(ev):
return ev["Author"] == "AUDIO_WRITER" and 's3://' in ev["Msg"]
return ev["Author"] == "AUDIO_WRITER" and "s3://" in ev["Msg"]
writer_events = list(filter(is_writer_uri_event, call_events))
s3_wav_url = re.search(r"(s3://.*)", writer_events[0]["Msg"]).groups(0)[0]
@ -268,8 +253,10 @@ def analyze(
meta = mongo_collection.find_one({"SystemID": cid})
duration = meta["EndTS"] - meta["StartTS"]
process_meta = process_call(meta)
data_points = get_data_points(process_meta['utter_events'], process_meta['first_event_fn'])
process_meta['data_points'] = data_points
data_points = get_data_points(
process_meta["utter_events"], process_meta["first_event_fn"]
)
process_meta["data_points"] = data_points
return {"url": uri, "meta": meta, "duration": duration, "process": process_meta}
def download_meta_audio():
@ -355,7 +342,7 @@ def analyze(
for dp in gen_data_values(saved_wav_path, data_points):
yield dp
asr_data_writer(call_asr_data, "call_alphanum", data_source())
asr_data_writer(call_asr_data, dataset_name, data_source())
def show_leaderboard():
def compute_user_stats(call_stat):
@ -383,14 +370,14 @@ def analyze(
leader_board = leader_df.rename(
columns={
"rank": "Rank",
"num_samples": "Codes",
"num_samples": "Count",
"name": "Name",
"samples_rate": "SpeechRate",
"duration_str": "Duration",
}
)[["Rank", "Name", "Codes", "Duration"]]
)[["Rank", "Name", "Count", "Duration"]]
print(
"""ASR Speller Dataset Leaderboard :
"""ASR Dataset Leaderboard :
---------------------------------"""
)
print(leader_board.to_string(index=False))

10
jasper/data/utils.py
View File

@ -104,10 +104,16 @@ class ExtendedPath(type(Path())):
return json.dump(data, jf, indent=2)
def get_mongo_conn(host="", port=27017):
def get_mongo_coll(uri="mongodb://localhost:27017/test.calls"):
ud = pymongo.uri_parser.parse_uri(uri)
conn = pymongo.MongoClient(uri)
return conn[ud['database']][ud['collection']]
def get_mongo_conn(host="", port=27017, db="test", col="calls"):
mongo_host = host if host else os.environ.get("MONGO_HOST", "localhost")
mongo_uri = f"mongodb://{mongo_host}:{port}/"
return pymongo.MongoClient(mongo_uri)
return pymongo.MongoClient(mongo_uri)[db][col]
def strip_silence(sound):

24
jasper/data/validation/process.py
View File

@ -24,6 +24,7 @@ def preprocess_datapoint(
import librosa.display
from pydub import AudioSegment
from nemo.collections.asr.metrics import word_error_rate
from jasper.client import transcribe_gen
try:
res = dict(sample)
@ -36,7 +37,7 @@ def preprocess_datapoint(
res["spoken"] = res["text"]
res["utterance_id"] = audio_path.stem
if not annotation_only:
from jasper.client import transcriber_pretrained, transcriber_speller
transcriber_pretrained = transcribe_gen(asr_port=8044)
aud_seg = (
AudioSegment.from_file_using_temporary_files(audio_path)
@ -49,6 +50,7 @@ def preprocess_datapoint(
[res["text"]], [res["pretrained_asr"]]
)
if use_domain_asr:
transcriber_speller = transcribe_gen(asr_port=8045)
res["domain_asr"] = transcriber_speller(aud_seg.raw_data)
res["domain_wer"] = word_error_rate(
[res["spoken"]], [res["pretrained_asr"]]
@ -74,19 +76,19 @@ def preprocess_datapoint(
@app.command()
def dump_validation_ui_data(
data_manifest_path: Path = typer.Option(
Path("./data/asr_data/call_alphanum/manifest.json"), show_default=True
dataset_path: Path = typer.Option(
Path("./data/asr_data/call_alphanum"), show_default=True
),
dump_path: Path = typer.Option(
Path("./data/valiation_data/ui_dump.json"), show_default=True
),
use_domain_asr: bool = True,
annotation_only: bool = True,
dump_name: str = typer.Option("ui_dump.json", show_default=True),
use_domain_asr: bool = False,
annotation_only: bool = False,
enable_plots: bool = True,
):
from concurrent.futures import ThreadPoolExecutor
from functools import partial
data_manifest_path = dataset_path / Path("manifest.json")
dump_path: Path = Path(f"./data/valiation_data/{dataset_path.stem}/{dump_name}")
plot_dir = data_manifest_path.parent / Path("wav_plots")
plot_dir.mkdir(parents=True, exist_ok=True)
typer.echo(f"Using data manifest:{data_manifest_path}")
@ -137,7 +139,7 @@ def dump_validation_ui_data(
@app.command()
def dump_corrections(dump_path: Path = Path("./data/valiation_data/corrections.json")):
col = get_mongo_conn().test.asr_validation
col = get_mongo_conn(col='asr_validation')
cursor_obj = col.find({"type": "correction"}, projection={"_id": False})
corrections = [c for c in cursor_obj]
@ -154,7 +156,7 @@ def fill_unannotated(
annotated_codes = {c["code"] for c in corrections}
all_codes = {c["gold_chars"] for c in processed_data}
unann_codes = all_codes - annotated_codes
mongo_conn = get_mongo_conn().test.asr_validation
mongo_conn = get_mongo_conn(col='asr_validation')
for c in unann_codes:
mongo_conn.find_one_and_update(
{"type": "correction", "code": c},
@ -232,7 +234,7 @@ def update_corrections(
def clear_mongo_corrections():
delete = typer.confirm("are you sure you want to clear mongo collection it?")
if delete:
col = get_mongo_conn().test.asr_validation
col = get_mongo_conn(col='asr_validation')
col.delete_many({"type": "correction"})
typer.echo("deleted mongo collection.")
typer.echo("Aborted")

5
jasper/data/validation/ui.py
View File

@ -9,7 +9,7 @@ app = typer.Typer()
if not hasattr(st, "mongo_connected"):
st.mongoclient = get_mongo_conn().test.asr_validation
st.mongoclient = get_mongo_conn(col='asr_validation')
mongo_conn = st.mongoclient
def current_cursor_fn():
@ -111,9 +111,8 @@ def main(manifest: Path):
if selected == "Inaudible":
corrected = ""
if st.button("Submit"):
correct_code = corrected.replace(" ", "").upper()
st.update_entry(
sample["utterance_id"], {"status": selected, "correction": correct_code}
sample["utterance_id"], {"status": selected, "correction": corrected}
)
st.update_cursor(sample_no + 1)
if correction_entry: