CER (Character Error Rate)¶
API reference for the cer module. For metric and evaluation documentation, see: CER
evaluatio.metrics.cer
¶
Character-level error metrics
This module provides utilities to compute character error rate (CER) and character-level edit distance between reference and hypothesis text sequences.
The functions accept any iterable of strings and internally convert them to a format compatible with the underlying native bindings.
Notes
- If a reference string is empty, the corresponding CER is defined as
inf. - These functions are thin wrappers around optimized native implementations.
character_error_rate_per_pair ¶
Compute character error rate (CER) for each reference-hypothesis pair.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
references
|
Iterable[str]
|
Iterable of reference strings. |
required |
hypotheses
|
Iterable[str]
|
Iterable of hypothesis strings. Must be the same length as
|
required |
Returns:
| Type | Description |
|---|---|
List[float]
|
Character error rate for each pair of reference and hypothesis. |
Raises:
| Type | Description |
|---|---|
ValueError
|
If the lists are of different lengths. |
See Also
metrics.uer.universal_error_rate_per_pair : Type-agnostic version.
Notes
- If a reference string is empty or contains no characters, the resulting
CER is
inf.
character_edit_distance_per_pair ¶
Compute character-level edit distance for each reference-hypothesis pair.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
references
|
Iterable[str]
|
Iterable of reference strings. |
required |
hypotheses
|
Iterable[str]
|
Iterable of hypothesis strings. Must be the same length as
|
required |
Returns:
| Type | Description |
|---|---|
List[int]
|
character-level edit distance for each pair. |
character_error_rate ¶
Compute the corpus level character error rate (CER) over all pairs.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
references
|
Iterable[str]
|
Iterable of reference strings. |
required |
hypotheses
|
Iterable[str]
|
Iterable of hypothesis strings. Must be the same length as
|
required |
Returns:
| Type | Description |
|---|---|
float
|
Corpus level character error rate across all pairs. |
Notes
- Equivalent to common CER implementations (e.g.,
jiwer-based metrics). - If all reference strings are empty, the resulting CER is
inf.
character_error_rate_ci ¶
Estimate a confidence interval for the character error rate via bootstrapping.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
references
|
Iterable[str]
|
Iterable of reference strings. |
required |
hypotheses
|
Iterable[str]
|
Iterable of hypothesis strings. Must be the same length as
|
required |
iterations
|
int
|
Number of bootstrap iterations. |
required |
alpha
|
float
|
Significance level for the confidence interval. |
required |
Returns:
| Type | Description |
|---|---|
ConfidenceInterval
|
Estimated confidence interval for the corpus level character error rate. |
Notes
- The bootstrapped metric corresponds to
character_error_rate. - If any reference string is empty or contains no characters, the resulting
CER can be
inf.