Automatic Speech Recognition
NeMo
Finnish
asr
speech-recognition
canary-v2
kenlm
finnish
Eval Results (legacy)
Instructions to use RASMUS/Finnish-ASR-Canary-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use RASMUS/Finnish-ASR-Canary-v2 with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("RASMUS/Finnish-ASR-Canary-v2") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
File size: 3,194 Bytes
cde7fe4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 | #ifndef DECODER_UTILS_H_
#define DECODER_UTILS_H_
#include <utility>
#include "fst/log.h"
#include "path_trie.h"
const float NUM_FLT_INF = std::numeric_limits<float>::max();
const float NUM_FLT_MIN = std::numeric_limits<float>::min();
// inline function for validation check
inline void check(
bool x, const char *expr, const char *file, int line, const char *err) {
if (!x) {
std::cout << "[" << file << ":" << line << "] ";
LOG(FATAL) << "\"" << expr << "\" check failed. " << err;
}
}
#define VALID_CHECK(x, info) \
check(static_cast<bool>(x), #x, __FILE__, __LINE__, info)
#define VALID_CHECK_EQ(x, y, info) VALID_CHECK((x) == (y), info)
#define VALID_CHECK_GT(x, y, info) VALID_CHECK((x) > (y), info)
#define VALID_CHECK_LT(x, y, info) VALID_CHECK((x) < (y), info)
// Function template for comparing two pairs
template <typename T1, typename T2>
bool pair_comp_first_rev(const std::pair<T1, T2> &a,
const std::pair<T1, T2> &b) {
return a.first > b.first;
}
// Function template for comparing two pairs
template <typename T1, typename T2>
bool pair_comp_second_rev(const std::pair<T1, T2> &a,
const std::pair<T1, T2> &b) {
return a.second > b.second;
}
// Return the sum of two probabilities in log scale
template <typename T>
T log_sum_exp(const T &x, const T &y) {
static T num_min = -std::numeric_limits<T>::max();
if (x <= num_min) return y;
if (y <= num_min) return x;
T xmax = std::max(x, y);
return std::log(std::exp(x - xmax) + std::exp(y - xmax)) + xmax;
}
// Get pruned probability vector for each time step's beam search
std::vector<std::pair<size_t, float>> get_pruned_log_probs(
const std::vector<double> &prob_step,
double cutoff_prob,
size_t cutoff_top_n);
// Get beam search result from prefixes in trie tree
std::vector<std::pair<double, std::string>> get_beam_search_result(
const std::vector<PathTrie *> &prefixes,
const std::vector<std::string> &vocabulary,
size_t beam_size,
std::vector<std::tuple<std::string, uint32_t, uint32_t>>& wordlist);
// Functor for prefix comparsion
bool prefix_compare(const PathTrie *x, const PathTrie *y);
/* Get length of utf8 encoding string
* See: http://stackoverflow.com/a/4063229
*/
size_t get_utf8_str_len(const std::string &str);
/* Split a string into a list of strings on a given string
* delimiter. NB: delimiters on beginning / end of string are
* trimmed. Eg, "FooBarFoo" split on "Foo" returns ["Bar"].
*/
std::vector<std::string> split_str(const std::string &s,
const std::string &delim);
/* Splits string into vector of strings representing
* UTF-8 characters (not same as chars)
*/
std::vector<std::string> split_utf8_str(const std::string &str);
// Add a word in index to the dicionary of fst
void add_word_to_fst(const std::vector<int> &word,
fst::StdVectorFst *dictionary);
// Add a word in string to dictionary
bool add_word_to_dictionary(
const std::string &word,
const std::unordered_map<std::string, int> &char_map,
bool add_space,
int SPACE_ID,
fst::StdVectorFst *dictionary);
#endif // DECODER_UTILS_H
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