"""Saraga Dataset Loader
.. admonition:: Dataset Info
:class: dropdown
This dataset contains time aligned melody, rhythm and structural annotations of Carnatic Music tracks, extracted
from the large open Indian Art Music corpora of CompMusic.
The dataset contains the following manual annotations referring to audio files:
- Section and tempo annotations stored as start and end timestamps together with the name of the section and
tempo during the section (in a separate file)
- Sama annotations referring to rhythmic cycle boundaries stored as timestamps.
- Phrase annotations stored as timestamps and transcription of the phrases using solfège symbols
({S, r, R, g, G, m, M, P, d, D, n, N}).
- Audio features automatically extracted and stored: pitch and tonic.
- The annotations are stored in text files, named as the audio filename but with the respective extension at the
end, for instance: "Bhuvini Dasudane.tempo-manual.txt".
The dataset contains a total of 249 tracks.
A total of 168 tracks have multitrack audio.
The files of this dataset are shared with the following license:
Creative Commons Attribution Non Commercial Share Alike 4.0 International
Dataset compiled by: Bozkurt, B.; Srinivasamurthy, A.; Gulati, S. and Serra, X.
For more information about the dataset as well as IAM and annotations, please refer to:
https://mtg.github.io/saraga/, where a really detailed explanation of the data and annotations is published.
"""
import csv
import json
from deprecated.sphinx import deprecated
import librosa
import numpy as np
from mirdata import annotations, core, download_utils, io, jams_utils
BIBTEX = """
@dataset{bozkurt_b_2018_4301737,
author = {Bozkurt, B. and
Srinivasamurthy, A. and
Gulati, S. and
Serra, X.},
title = {Saraga: research datasets of Indian Art Music},
month = may,
year = 2018,
publisher = {Zenodo},
version = {1.5},
doi = {10.5281/zenodo.4301737},
url = {https://doi.org/10.5281/zenodo.4301737}
}
"""
INDEXES = {
"default": "1.5",
"test": "1.5",
"1.5": core.Index(filename="saraga_carnatic_index_1.5.json"),
}
REMOTES = {
"all": download_utils.RemoteFileMetadata(
filename="saraga1.5_carnatic.zip",
url="https://zenodo.org/record/4301737/files/saraga1.5_carnatic.zip?download=1",
checksum="e4fcd380b4f6d025964cd16aee00273d",
)
}
LICENSE_INFO = (
"Creative Commons Attribution Non Commercial Share Alike 4.0 International."
)
[docs]
class Track(core.Track):
"""Saraga Track Carnatic class
Args:
track_id (str): track id of the track
data_home (str): Local path where the dataset is stored. default=None
If `None`, looks for the data in the default directory, `~/mir_datasets`
Attributes:
audio_path (str): path to audio file
audio_ghatam_path (str): path to ghatam audio file
audio_mridangam_left_path (str): path to mridangam left audio file
audio_mridangam_right_path (str): path to mridangam right audio file
audio_violin_path (str): path to violin audio file
audio_vocal_s_path (str): path to vocal s audio file
audio_vocal_pat (str): path to vocal pat audio file
ctonic_path (srt): path to ctonic annotation file
pitch_path (srt): path to pitch annotation file
pitch_vocal_path (srt): path to vocal pitch annotation file
tempo_path (srt): path to tempo annotation file
sama_path (srt): path to sama annotation file
sections_path (srt): path to sections annotation file
phrases_path (srt): path to phrases annotation file
metadata_path (srt): path to metadata file
Cached Properties:
tonic (float): tonic annotation
pitch (F0Data): pitch annotation
pitch_vocal (F0Data): vocal pitch annotation
tempo (dict): tempo annotations
sama (BeatData): sama section annotations
sections (SectionData): track section annotations
phrases (SectionData): phrase annotations
metadata (dict): track metadata with the following fields:
- title (str): Title of the piece in the track
- mbid (str): MusicBrainz ID of the track
- album_artists (list, dicts): list of dicts containing the album artists present in the track and its mbid
- artists (list, dicts): list of dicts containing information of the featuring artists in the track
- raaga (list, dict): list of dicts containing information about the raagas present in the track
- form (list, dict): list of dicts containing information about the forms present in the track
- work (list, dicts): list of dicts containing the work present in the piece, and its mbid
- taala (list, dicts): list of dicts containing the talas present in the track and its uuid
- concert (list, dicts): list of dicts containing the concert where the track is present and its mbid
"""
def __init__(self, track_id, data_home, dataset_name, index, metadata):
super().__init__(track_id, data_home, dataset_name, index, metadata)
# Audio path
self.audio_path = self.get_path("audio-mix")
# Multitrack audio paths
self.audio_ghatam_path = self.get_path("audio-ghatam")
self.audio_mridangam_left_path = self.get_path("audio-mridangam-left")
self.audio_mridangam_right_path = self.get_path("audio-mridangam-right")
self.audio_violin_path = self.get_path("audio-violin")
self.audio_vocal_s_path = self.get_path("audio-vocal-s")
self.audio_vocal_path = self.get_path("audio-vocal")
# Annotation paths
self.ctonic_path = self.get_path("ctonic")
self.pitch_path = self.get_path("pitch")
self.pitch_vocal_path = self.get_path("pitch-vocal")
self.tempo_path = self.get_path("tempo")
self.sama_path = self.get_path("sama")
self.sections_path = self.get_path("sections")
self.phrases_path = self.get_path("phrases")
self.metadata_path = self.get_path("metadata")
@core.cached_property
def metadata(self):
return load_metadata(self.metadata_path)
@core.cached_property
def tonic(self):
return load_tonic(self.ctonic_path)
@core.cached_property
def pitch(self):
return load_pitch(self.pitch_path)
@core.cached_property
def pitch_vocal(self):
return load_pitch(self.pitch_vocal_path)
@core.cached_property
def tempo(self):
return load_tempo(self.tempo_path)
@core.cached_property
def sama(self):
return load_sama(self.sama_path)
@core.cached_property
def sections(self):
return load_sections(self.sections_path)
@core.cached_property
def phrases(self):
return load_phrases(self.phrases_path)
@property
def audio(self):
"""The track's audio
Returns:
* np.ndarray - audio signal
* float - sample rate
"""
return load_audio(self.audio_path)
[docs]
def to_jams(self):
"""Get the track's data in jams format
Returns:
jams.JAMS: the track's data in jams format
"""
return jams_utils.jams_converter(
audio_path=self.audio_path,
beat_data=[(self.sama, "sama")],
f0_data=[(self.pitch, "pitch"), (self.pitch_vocal, "pitch_vocal")],
section_data=[(self.sections, "sections")],
event_data=[(self.phrases, "phrases")],
metadata={
"tempo": self.tempo,
"tonic": self.tonic,
"metadata": self.metadata,
},
)
# no decorator here because of https://github.com/librosa/librosa/issues/1267
[docs]
def load_audio(audio_path):
"""Load a Saraga Carnatic audio file.
Args:
audio_path (str): path to audio file
Returns:
* np.ndarray - the mono audio signal
* float - The sample rate of the audio file
"""
if audio_path is None:
return None
return librosa.load(audio_path, sr=44100, mono=False)
[docs]
@io.coerce_to_string_io
def load_tonic(fhandle):
"""Load track absolute tonic
Args:
fhandle (str or file-like): Local path where the tonic path is stored.
Returns:
int: Tonic annotation in Hz
"""
reader = csv.reader(fhandle, delimiter="\t")
tonic = float(next(reader)[0])
return tonic
[docs]
@io.coerce_to_string_io
def load_pitch(fhandle):
"""Load pitch
Args:
fhandle (str or file-like): Local path where the pitch annotation is stored.
Returns:
F0Data: pitch annotation
"""
times = []
freqs = []
reader = csv.reader(fhandle, delimiter="\t")
for line in reader:
times.append(float(line[0]))
freqs.append(float(line[1]))
if not times:
return None
times = np.array(times)
freqs = np.array(freqs)
voicing = (freqs > 0).astype(float)
return annotations.F0Data(times, "s", freqs, "hz", voicing, "binary")
[docs]
@io.coerce_to_string_io
def load_tempo(fhandle):
"""Load tempo from carnatic collection
Args:
fhandle (str or file-like): Local path where the tempo annotation is stored.
Returns:
dict: Dictionary of tempo information with the following keys:
- tempo_apm: tempo in aksharas per minute (APM)
- tempo_bpm: tempo in beats per minute (BPM)
- sama_interval: median duration (in seconds) of one tāla cycle
- beats_per_cycle: number of beats in one cycle of the tāla
- subdivisions: number of aksharas per beat of the tāla
"""
tempo_annotation = {}
reader = csv.reader(fhandle, delimiter=",")
tempo_data = next(reader)
tempo_apm = tempo_data[0]
tempo_bpm = tempo_data[1]
sama_interval = tempo_data[2]
beats_per_cycle = tempo_data[3]
subdivisions = tempo_data[4]
if "NaN" in tempo_data or " NaN" in tempo_data or "NaN " in tempo_data:
return None
tempo_annotation["tempo_apm"] = (
float(tempo_apm) if "." in tempo_apm else int(tempo_apm)
)
tempo_annotation["tempo_bpm"] = (
float(tempo_bpm) if "." in tempo_bpm else int(tempo_bpm)
)
tempo_annotation["sama_interval"] = (
float(sama_interval) if "." in sama_interval else int(sama_interval)
)
tempo_annotation["beats_per_cycle"] = (
float(beats_per_cycle) if "." in beats_per_cycle else int(beats_per_cycle)
)
tempo_annotation["subdivisions"] = (
float(subdivisions) if "." in subdivisions else int(subdivisions)
)
return tempo_annotation
[docs]
@io.coerce_to_string_io
def load_sama(fhandle):
"""Load sama
Args:
fhandle (str or file-like): Local path where the sama annotation is stored.
Returns:
BeatData: sama annotations
"""
beat_times = []
beat_positions = []
idx = 1
reader = csv.reader(fhandle, delimiter="\t")
for line in reader:
beat_times.append(float(line[0]))
beat_positions.append(idx)
idx += 1
if not beat_times or beat_times[0] == -1.0:
return None
return annotations.BeatData(
np.array(beat_times), "s", np.array(beat_positions), "global_index"
)
[docs]
@io.coerce_to_string_io
def load_sections(fhandle):
"""Load sections from carnatic collection
Args:
fhandle (str or file-like): Local path where the section annotation is stored.
Returns:
SectionData: section annotations for track
"""
intervals = []
section_labels = []
reader = csv.reader(fhandle, delimiter="\t")
for line in reader:
if line != "\n":
intervals.append([float(line[0]), float(line[0]) + float(line[2])])
section_labels.append(str(line[3]))
if not intervals:
return None
return annotations.SectionData(np.array(intervals), "s", section_labels, "open")
[docs]
@io.coerce_to_string_io
def load_phrases(fhandle):
"""Load phrases
Args:
fhandle (str or file-like): Local path where the phrase annotation is stored.
Returns:
EventData: phrases annotation for track
"""
start_times = []
end_times = []
events = []
reader = csv.reader(fhandle, delimiter="\t")
for line in reader:
start_times.append(float(line[0]))
end_times.append(float(line[0]) + float(line[2]))
if len(line) == 4:
events.append(str(line[3].split("\n")[0]))
else:
events.append("")
if not start_times:
return None
return annotations.EventData(
np.array([start_times, end_times]).T, "s", events, "open"
)
[docs]
@core.docstring_inherit(core.Dataset)
class Dataset(core.Dataset):
"""
The saraga_carnatic dataset
"""
def __init__(self, data_home=None, version="default"):
super().__init__(
data_home,
version,
name="saraga_carnatic",
track_class=Track,
bibtex=BIBTEX,
indexes=INDEXES,
remotes=REMOTES,
license_info=LICENSE_INFO,
)
[docs]
@deprecated(
reason="Use mirdata.datasets.saraga_carnatic.load_audio", version="0.3.4"
)
def load_audio(self, *args, **kwargs):
return load_audio(*args, **kwargs)
[docs]
@deprecated(
reason="Use mirdata.datasets.saraga_carnatic.load_tonic", version="0.3.4"
)
def load_tonic(self, *args, **kwargs):
return load_tonic(*args, **kwargs)
[docs]
@deprecated(
reason="Use mirdata.datasets.saraga_carnatic.load_pitch", version="0.3.4"
)
def load_pitch(self, *args, **kwargs):
return load_pitch(*args, **kwargs)
[docs]
@deprecated(
reason="Use mirdata.datasets.saraga_carnatic.load_tempo", version="0.3.4"
)
def load_tempo(self, *args, **kwargs):
return load_tempo(*args, **kwargs)
[docs]
@deprecated(
reason="Use mirdata.datasets.saraga_carnatic.load_sama", version="0.3.4"
)
def load_sama(self, *args, **kwargs):
return load_sama(*args, **kwargs)
[docs]
@deprecated(
reason="Use mirdata.datasets.saraga_carnatic.load_sections", version="0.3.4"
)
def load_sections(self, *args, **kwargs):
return load_sections(*args, **kwargs)
[docs]
@deprecated(
reason="Use mirdata.datasets.saraga_carnatic.load_phrases", version="0.3.4"
)
def load_phrases(self, *args, **kwargs):
return load_phrases(*args, **kwargs)